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At least 757 records · Page 42Linked to original sources

USGS2010

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Journal of Applied Statistics↗

USGS1985

Study and interpretation of the chemical characteristics of natural water

The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from human activities. Broad interrelationships among these processes and their effects can be discerned by application of principles of chemical thermodynamics. Some of the processes of solution or precipitation of minerals can be closely evaluated by means of principles of chemical equilibrium, including the law of mass action and the Nernst equation. Other processes are irreversible and require consideration of reaction mechanisms and rates. The chemical composition of the crustal rocks of the Earth and the composition of the ocean and the atmosphere are significant in evaluating sources of solutes in natural freshwater. The ways in which solutes are taken up or precipitated and the amounts present in solution are influenced by many environmental factors, especially climate, structure and position of rock strata, and biochemical effects associated with life cycles of plants and animals, both microscopic and macroscopic. Taken together and in application with the further influence of the general circulation of all water in the hydrologic cycle, the chemical principles and environmental factors form a basis for the developing science of natural-water chemistry. Fundamental data used in the determination of water quality are obtained by the chemical analysis of water samples in the laboratory or onsite sensing of chemical properties in the field. Sampling is complicated by changes in the composition of moving water and by the effects of particulate suspended material. Some constituents are unstable and require onsite determination or sample preservation. Most of the constituents determined are reported in gravimetric units, usually milligrams per liter or milliequivalents per liter. More than 60 constituents and properties are included in water analyses frequently enough to provide a basis for consideration of the sources from which each is generally derived, the most probable forms of elements and ions in solution, solubilitycontrols, expected concentration ranges, and other chemical factors. Mechanisms that control concentrations of elements commonly present in amounts less than a few tens of micrograms per liter cannot always be easily ascertained, but present information suggests that many are controlled by solubility of their hydroxides or carbonates or by sorption on solid particles. Many dissolved organic compounds can now be specifically determined. Chemical analyses may be grouped and statistically evaluated by means, medians, frequency distributions, or ion correlations to summarize large volumes of data. Graphing of analyses or of groups of analyses aids in showing chemical relationships among water, probable sources of solutes, areal water-quality regimen, temporal and spatial variation, and water-resources evaluation. Graphs may show water type based on chemical composition, relationships among ions, or groups of ions in individual waters or many waters considered simultaneously. The relationships of water quality to hydrogeologic characteristics, such as stream discharge rate or ground-water flow patterns, can be shown by mathematical equations, graphs, and maps. About 80 water analyses selected from the literature are tabulated to illustrate the relationships described, and some of these, along with many others that are not tabulated, are also used in demonstrating graphing and mapping techniques. Relationships of water composition to source rock type are illustrated by graphs of some of the tabulated analyses. Human activities may modify water composition extensively through direct effects of pollution and indirect results of water development, such as intrusion of seawater in groundwater aquifers. Water-quality standards for domestic, agricultural, and industrial use have been published by various agencies. Irrigation project requirements for water quality are particularly intricate. Fundamental knowledge of processes that control natural-water composition is required for rational management of water quality.

Water Supply Paper↗

USGS2021

Assessment of contaminant trends in plumes and wells and monitoring network optimization at the Badger Army Ammunition Plant, Sauk County, Wisconsin

Soil and groundwater at the Badger Army Ammunition Plant (BAAP), Sauk County, Wisconsin, were affected by several contaminants as a result of production and waste disposal practices common during its operation from 1942 to 1975. Three distinct plumes of contaminated groundwater originate on BAAP property and extend off-site, as identified by previous studies. Routine sampling of groundwater quality from a network of monitoring wells and off-site private wells has been performed since 1990, although the number of wells monitored and the monitoring frequency have varied as the approved monitoring plan was modified. During the period of monitoring from 1990 to 2018, numerous site investigations and remedial actions were conducted to address the sources of contamination, contaminated soils, and groundwater. Concentrations of contaminants reportedly decreased between 2000 and 2012 within all three plumes. Five or six contaminants of concern (COCs) were identified for each of the three plumes. An independent assessment of the contaminant plumes and of the monitoring network was conducted using groundwater-quality data collected from more than 600 wells between 2000 and 2018. In a study conducted by the U.S. Geological Survey (USGS), in cooperation with the Army Environmental Command, a consistent data aggregation and interpolation scheme was applied to derive the likely maximum groundwater plume extents in four 3-year time periods between 2000 and 2018. The plume extent was defined by the Enforcement Standard for each COC and represents the maximum concentration observed in each 3-year time period. The plume boundary analysis shows that the spatial extent of groundwater contamination decreased for most COCs during the study period. Some plume boundaries are not well delineated by the existing monitoring network, particularly the downgradient edge of the Propellant Burning Ground plume. Maps identify the plume boundary in each time period, the sampling well network used to delineate the plume, and wells that were sampled in the 2010–12 period but not sampled in the 2015–18 period. A series of statistical analyses using the Monitoring and Remediation Optimization System, version 3.0, program were applied to the available COC concentration data for two distinct periods, 2000 to 2012 and 2013 to 2018, with the break between periods coinciding with changes to the monitoring network in 2013. Trends in the concentration of COCs in individual wells varied, although generally more wells had decreasing than had increasing concentrations for most COCs in both time periods. The exceptions were ethyl ether in the 2004–12 period and 2,6-dinitrotoluene in the 2013–18 period, for which more wells had an increasing trend. Spatial moment analysis of concentration data from the well network was used to assess the stability of each plume for the COCs. During the 2000–12 period, most of the contaminant plumes for which data were sufficient to complete the analysis were either decreasing or stable in mass and size. The exceptions were carbon tetrachloride (associated solely with the Propellant Burning Ground plume) and 2,4-dinitrotoluene and 2,6-dinitrotoluene (in the Deterrent Burning Ground plume), which showed an increasing trend in mass. No COCs showed an increasing trend in plume mass in the 2013–18 period. Some wells with increasing trends in concentration or with concentrations greater than the enforcement standard are near the tail of a plume, where increased monitoring may be of value to better define future plume boundaries. A spatial optimization analysis covering the 2013–18 period identified six wells that provided information redundant to that from other wells. A temporal optimization analysis identified optimal sampling frequencies for 125 wells. Remedial actions directed at the Propellant Burning Ground plume coincided with a general decrease in plume mass and size, although in specific areas and depths, the plume size for specific contaminants may still be increasing.

Wisconsin↗

USGS2022

U.S. Geological Survey Hydrologic Toolbox — A graphical and mapping interface for analysis of hydrologic data

The Hydrologic Toolbox is a Windows-based desktop software program that provides a graphical and mapping interface for analysis of hydrologic time-series data with a set of widely used and standardized computational methods. The software combines the analytical and statistical functionality provided in the U.S. Geological Survey Groundwater and Surface-Water Toolboxes and provides several enhancements to these programs. The main analytical methods are the computation of hydrologic-frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10); the computation of design flows, including biologically based flows; the computation of flow-duration curves and duration hydrographs; eight computer-programming methods for hydrograph separation of a streamflow time series, including the Base-Flow Index (BFI), HYSEP, PART, and SWAT Bflow methods and Eckhardt’s two-parameter digital-filtering method; and the RORA recession-curve displacement method and associated RECESS program to estimate groundwater-recharge values from streamflow data. Several of the statistical methods provided in the Hydrologic Toolbox are used primarily for computation of critical low-flow statistics. The Hydrologic Toolbox also facilitates retrieval of streamflow and groundwater-level time-series data from the U.S. Geological Survey National Water Information System and outputs text reports that describe their analyses. The Hydrologic Toolbox was developed by use of the DotSpatial geographic information system (GIS) programming library, which is part of the MapWindow project. DotSpatial is a nonproprietary, open-source program written for the .NET framework that includes a spatial data viewer and GIS capabilities. Advantages of the DotSpatial system include its pure .NET implementation for both the user interface and the GIS mapping engine, and thus the DotSpatial system simplifies software deployment and installation. In addition to combining the functionality of the separate Groundwater and Surface-Water Toolboxes, the Hydrologic Toolbox also organizes the functionality by theme (Groundwater Tools, Surface-Water Tools, and general Time-Series Tools). This report provides a description of how to build a Hydrologic Toolbox project and to download and manage hydrologic time-series data. It includes an overview of the analytical and statistical capabilities of the Hydrologic Toolbox and highlights the primary differences between the Hydrologic Toolbox and the Groundwater and Surface-Water Toolboxes. The report supplements information available in an extensive online Help manual and is intended to provide a set of instructions that will allow users to quickly develop skills to use the mapping, data-retrieval, and computational tools of the program.

Techniques and Methods↗

USGS2024

Assessing giant sequoia mortality and regeneration following high-severity wildfire

Fire is a critical driver of giant sequoia ( Sequoiadendron giganteum [Lindl.] Buchholz) regeneration. However, fire suppression combined with the effects of increased temperature and severe drought has resulted in fires of an intensity and size outside of the historical norm. As a result, recent mega-fires have killed a significant portion of the world's sequoia population (13%–19%), and uncertainty surrounds whether severely affected groves will be able to recover naturally, potentially leading to a loss of grove area. To assess the likelihood of natural recovery, we collected spatially explicit data assessing mortality, crown condition, and regeneration within four giant sequoia groves that were severely impacted by the SQF- (2020) and KNP-Complex (2021) wildfires within Sequoia and Kings Canyon National Parks. In total, we surveyed 5.9 ha for seedlings and assessed the crown condition of 1104 giant sequoias. To inform management, we used a statistical methodology that robustly quantifies the uncertainty in inherently “noisy” seedling data and takes advantage of readily available remote sensing metrics that would make our findings applicable to other recently burned groves. A loss of giant sequoia grove area would be a consequence of giant sequoia tree mortality followed by a failure of natural regeneration. We found that areas that experienced very high-severity fire (above ~800 RdNBR) are at substantial risk for the loss of grove area, with tree mortality rapidly increasing and giant sequoia seedling density simultaneously decreasing with fire severity. Such high-severity areas comprised 17.8, 142.0, 14.6, 1.6 ha and ~90%, ~14%, ~53%, and ~27% of Board Camp, Redwood Mountain, Suwanee, and New Oriole Lake groves, respectively. In all sampling areas, we found that seedling densities fell far below the average density measured after prescribed fires, where seedling numbers were almost certainly adequate to maintain giant sequoia populations and postfire conditions were more in keeping with historical norms. Importantly, spatial pattern is also important in assessing the risk of grove loss, and in two groves, Suwanee and New Oriole Lake, the high-severity patches were not always contiguous, potentially making some areas more resilient to regeneration failure due to the proximity of surviving trees.

Ecosphere↗

USGS2021

Improved fire severity mapping in the North American boreal forest using a hybrid composite method

Fire severity is a key driver shaping the ecological structure and function of North American boreal ecosystems, a biome dominated by large, high-intensity wildfires. Satellite-derived burn severity maps have been an important tool in these remote landscapes for both fire and resource management. The conventional methodology to produce satellite-inferred fire severity maps generally involves comparing imagery from 1 year before and 1 year after a fire, yet environmental conditions unique to the boreal have limited the accuracy of resulting products. We introduce an alternative method – the ‘hybrid composite’ – based on deriving mean severity over time on a per-pixel basis within the cloud-computing environment of Google Earth Engine. It constructs the post-fire image from satellite data composited from all valid images (i.e., clear-sky and snow-free) acquired in the time period immediately after fire through the early growing season of the following year. We compare this approach to paired-scene and composite approaches where the post-fire time period is from the growing season 1 year after fire. Validation statistics based on field-derived data for 52 fires across Alaska and Canada indicate that the hybrid composite method outperforms the other approaches. This approach presents an efficient and cost-effective means to monitor and explore trends and patterns across broad spatial domains, and could be applied to fires in other regions, especially those with frequent cloud cover or rapid vegetation recovery.

Alaska↗

USGS2014

Spatially explicit modeling to evaluate regional stream water quality

Spatially referenced regressions on watershed attributes (SPARROW) models have been developed and applied over the past two decades to address the need for large-scale, spatially explicit information on stream water quality conditions. The strength of SPARROW models is that they describe the primary environmental processes that affect the supply and transport of contaminant mass in watersheds, based on the use of stream monitoring and geospatial data to statistically estimate model parameters. SPARROW models were first applied at the scale of the conterminous US, but their use has grown through applications in many smaller regions of the US and in other countries. Recent developments include a web-based decision support system that provides open access to model results without the assistance of technical experts or special software. As it is highlighted in this chapter, SPARROW modeling provides a flexible framework for studying many aspects of water quality to support both research and resource management objectives.

Book chapter↗

USGS2002

Estimation of shoreline position and change using airborne topographic lidar data

A method has been developed for estimating shoreline position from airborne scanning laser data. This technique allows rapid estimation of objective, GPS-based shoreline positions over hundreds of kilometers of coast, essential for the assessment of large-scale coastal behavior. Shoreline position, defined as the cross-shore position of a vertical shoreline datum, is found by fitting a function to cross-shore profiles of laser altimetry data located in a vertical range around the datum and then evaluating the function at the specified datum. Error bars on horizontal position are directly calculated as the 95% confidence interval on the mean value based on the Student's t distribution of the errors of the regression. The technique was tested using lidar data collected with NASA's Airborne Topographic Mapper (ATM) in September 1997 on the Outer Banks of North Carolina. Estimated lidar-based shoreline position was compared to shoreline position as measured by a ground-based GPS vehicle survey system. The two methods agreed closely with a root mean square difference of 2.9 m. The mean 95% confidence interval for shoreline position was ?? 1.4 m. The technique has been applied to a study of shoreline change on Assateague Island, Maryland/Virginia, where three ATM data sets were used to assess the statistics of large-scale shoreline change caused by a major 'northeaster' winter storm. The accuracy of both the lidar system and the technique described provides measures of shoreline position and change that are ideal for studying storm-scale variability over large spatial scales.

Maryland, North Carolina, Virginia↗

USGS2012

Surface-water radon-222 distribution along the west-central Florida shelf

In February 2009 and August 2009, the spatial distribution of radon-222 in surface water was mapped along the west-central Florida shelf as collaboration between the Response of Florida Shelf Ecosystems to Climate Change project and a U.S. Geological Survey Mendenhall Research Fellowship project. This report summarizes the surface distribution of radon-222 from two cruises and evaluates potential physical controls on radon-222 fluxes. Radon-222 is an inert gas produced overwhelmingly in sediment and has a short half-life of 3.8 days; activities in surface water ranged between 30 and 170 becquerels per cubic meter. Overall, radon-222 activities were enriched in nearshore surface waters relative to offshore waters. Dilution in offshore waters is expected to be the cause of the low offshore activities. While thermal stratification of the water column during the August survey may explain higher radon-222 activities relative to the February survey, radon-222 activity and integrated surface-water inventories decreased exponentially from the shoreline during both cruises. By estimating radon-222 evasion by wind from nearby buoy data and accounting for internal production from dissolved radium-226, its radiogenic long-lived parent, a simple one-dimensional model was implemented to determine the role that offshore mixing, benthic influx, and decay have on the distribution of excess radon-222 inventories along the west Florida shelf. For multiple statistically based boundary condition scenarios (first quartile, median, third quartile, and maximum radon-222 inshore of 5 kilometers), the cross-shelf mixing rates and average nearshore submarine groundwater discharge (SGD) rates varied from 100.38 to 10-3.4 square kilometers per day and 0.00 to 1.70 centimeters per day, respectively. This dataset and modeling provide the first attempt to assess cross-shelf mixing and SGD on such a large spatial scale. Such estimates help scale up SGD rates that are often made at 1- to 10-meter resolution to a coarser but more regionally applicable scale of 1- to 10-kilometer resolution. More stringent analyses and model evaluation are required, but results and analyses presented in this report provide the foundation for conducting a more rigorous statistical assessment.

Florida↗

USGS1987

Statistical analysis of surface-water-quality data in and near the coal-mining region of southwestern Indiana, 1957-80

The Surface Mining Control and Reclamation Act of 1977 requires that applications for coal-mining permits contain information about the water quality of streams at and near a proposed mine. To meet this need for information, streamflow, specific conductance, pH, and concentrations of total alkalinity, sulfate, dissolved solids, suspended solids, total iron, and total manganese at 37 stations were analyzed to determine the spatial and seasonal variations in water quality and to develop equations for predicting water quality. The season of lowest median streamflow was related to the size of the drainage area. Median streamflow was least during fall at 15 of 16 stations having drainage areas greater than 1,000 square miles but was least during summer at 17 of 21 stations having drainage areas less than 1,000 square miles. In general, the season of lowest median specific conductance occurred during the season of highest streamflow except at stations on the Wabash River. Median specific conductance was least during summer at 9 of 9 stations on the Wabash River, but was least during winter or spring (the seasons of highest streamflow) at 27 of the remaining 28 stations. Linear, inverse, semilog, log-log, and hyperbolic regression models were used to investigate the functional relations between water-quality characteristics and streamflow. Of 186 relations investigated, 143 were statistically significant. Specific conductance and concentrations of total alkalinity and sulfate were negatively related to streamflow at all stations except for a positive relation between total alkalinity concentration and streamflow at Patoka River near Princeton. Concentrations of total alkalinity and sulfate were positively related to specific conductance at all stations except for a negative relation at Patoka River near Princeton and for a positive and negative relation at Patoka River at Jasper. Most of these relations are good, have small confidence intervals, and will give reliable predictions of the water-quality variables listed above. The poorest relations are typically at stations in the Patoka River watershed. Suspended-solids concentration was positively related to streamflow at all but two stations on the Patoka River. These relations are poor, have large confidence intervals, and will give less reliable predictions of suspended-solids concentration. Predictive equations for the regional relations between dissolved-solids concentration and specific conductance and between sulfate concentration and specific conductance, and the seasonal patterns of water quality, are probably valid for the coal-mining regions of Illinois and western Kentucky.

Indiana↗

USGS2013

Descriptive models, grade-tonnage relations, and databases for the assessment of sediment-hosted copper deposits: with emphasis on deposits in the Central Africa Copperbelt, Democratic Republic of the Congo and Zambia: Chapter J in Global mineral resource assessment

The Central African Copperbelt (CACB) is one of the most important copper-producing regions of the world. The majority of copper produced in Africa comes from this region defined by the Neoproterozoic Katanga sedimentary basin of the southern Democratic Republic of the Congo (DRC) and northern Zambia. Copper in the CACB is mined from sediment-hosted stratabound copper deposits associated with red beds and includes the giant deposits in the Kolwezi and Tenge-Fungurume districts in the DRC and the Konkola-Musoshi and Nchanga-Chingola districts in Zambia. In recent years, sediment-hosted structurally controlled replacement and vein (SCRV) copper deposits, such as the giant Kansanshi deposit in Zambia have become important exploration targets in the CACB region. In 2011, the CACB accounted for 7.2 percent of the estimated global mine production of copper. Global production of copper is principally derived from porphyry and sediment-hosted copper deposits (57 and 23 percent, respectively). Almost 50 percent of the copper known to exist in sediment-hosted deposits (past production plus identified resources) is contained in the CACB, 25 percent is contained in the Zechstein Basin of northern Europe, and the remainder is contained in an additional 29 sedimentary basins distributed around the globe. The U.S. Geological Survey (USGS) led an assessment of undiscovered copper resources in the CACB as part of a global mineral resource assessment for undiscovered resources of potash, copper, and platinum-group elements in selected mineral deposit types. As part of the assessment process, available data for the CACB were compiled and evaluated. This report describes the results of that work, including new descriptive mineral-deposit and grade and tonnage models and spatial databases for deposits and occurrences, ore bodies and open pits. Chapter 1 of this report summarizes a descriptive model of sediment-hosted stratabound copper deposits. General characteristics and subtypes of sediment-hosted stratabound copper deposits are described based upon worldwide examples. Chapter 2 provides a global database of 170 sediment-hosted copper deposits, along with a statistical evaluation of grade and tonnage data for stratabound deposits, a comparison of stratabound deposits in the CACB with those found elsewhere, a discussion of the distinctive characteristics of the subtypes of sediment-hosted copper deposits that occur within the CACB, and guidelines for using grade and tonnage distributions for assessment of undiscovered resources in sediment-hosted stratabound deposits in the CACB. Chapter 3 presents a new descriptive model of sediment-hosted structurally controlled replacement and vein (SCRV) copper deposits with descriptions of individual deposits of this type in the CACB and elsewhere. Appendix A describes a relational database of tonnage, grade, and other information for more than 100 sediment-hosted copper deposits in the CACB. These data are used to calculate the pre-mining mineral endowment for individual deposits in the CACB and serve as the basis for the grade and tonnage models presented in chapter 2. Appendix B describes three spatial databases (Esri shapefiles) for (1) point locations of more than 500 sediment-hosted copper deposits and prospects, (2) projected surface extent of 86 selected copper ore bodies, and (3) areal extent of 77 open pits, all within the CACB.

Scientific Investigations Report↗

USGS2016

Statistical analysis and mapping of water levels in the Biscayne aquifer, water conservation areas, and Everglades National Park, Miami-Dade County, Florida, 2000–2009

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000–2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000–2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990–1999 and 2000–2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974–2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990–1999 and 2000–2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990–1999 and 2000–2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000–2009 than during 1990–1999; and that inland water levels were generally lower during 2000–2009 than during 1990–1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000–2009 than during 1990–1999. Mean October water levels during 2000–2009 were generally higher than during 1990–1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

Florida↗

USGS2008

The use of local indicators of spatial association to improve LiDAR-derived predictions of potential amphibian breeding ponds

We examined whether spatially explicit information improved models that use LiDAR return signal intensity to discriminate in-pond habitat from terrestrial habitat at 24 amphibian breeding ponds. The addition of Local Indicators of Spatial Association (LISA) to LiDAR return intensity data significantly improved predictive models at all ponds, reduced residual error by as much as 74%, and appeared to improve models by reducing classification errors associated with types of in-pond vegetation. We conclude that LISA statistics can help maximize the information content that can be extracted from time resolved LiDAR return data in models that predict the occurrence of small, seasonal ponds. ?? Springer-Verlag 2008.

Journal of Geographical Systems↗

USGS2006

A multivariate model of plant species richness in forested systems: Old-growth montane forests with a long history of fire

Recently, efforts to develop multivariate models of plant species richness have been extended to include systems where trees play important roles as overstory elements mediating the influences of environment and disturbance on understory richness. We used structural equation modeling to examine the relationship of understory vascular plant species richness to understory abundance, forest structure, topographic slope, and surface fire history in lower montane forests on the North Rim of Grand Canyon National Park, USA based on data from eighty-two 0.1 ha plots. The questions of primary interest in this analysis were: (1) to what degree are influences of trees on understory richness mediated by effects on understory abundance? (2) To what degree are influences of fire history on richness mediated by effects on trees and/or understory abundance? (3) Can the influences of fire history on this system be related simply to time-since-fire or are there unique influences associated with long-term fire frequency? The results we obtained are consistent with the following inferences. First, it appears that pine trees had a strong inhibitory effect on the abundance of understory plants, which in turn led to lower understory species richness. Second, richness declined over time since the last fire. This pattern appears to result from several processes, including (1) a post-fire stimulation of germination, (2) a decline in understory abundance, and (3) an increase over time in pine abundance (which indirectly leads to reduced richness). Finally, once time-since-fire was statistically controlled, it was seen that areas with higher fire frequency have lower richness than expected, which appears to result from negative effects on understory abundance, possibly by depletions of soil nutrients from repeated surface fire. Overall, it appears that at large temporal and spatial scales, surface fire plays an important and complex role in structuring understory plant communities in old-growth montane forests. These results show how multivariate models of herbaceous richness can be expanded to apply to forested systems. Copyright ?? Oikos 2006.

Oikos↗

USGS2006

Multiscale patterns of movement in fragmented landscapes and consequences on demography of the snail kite in Florida

1. Habitat loss and fragmentation are major factors affecting vertebrate populations. A major effect of these habitat alterations is that they reduce movement of organisms. Despite the accepted importance of movement in driving the dynamics of many natural populations, movement of vertebrates in fragmented landscapes have seldom been estimated with robust statistical methods. 2. We estimated movement probabilities of snail kites Rosthramus sociabilis within the remaining wetlands in Florida. Using both radio-telemetry and banding information, we used a multistate modelling approach to estimate transition probabilities at two temporal scales (month; year) and multiple spatial scales. We examined kite movement among wetlands altered by three different levels of fragmentation: among wetlands separated by small physical barriers (e.g. road); among wetlands separated by moderate amount of matrix (< 5 km); and among wetlands separated by extensive matrix areas (> 15 km). 3. Kites moved extensively among contiguous wetlands (movement probability 0?29 per month), but significantly less among isolated wetlands (movement probability 0?10 per month). 4. Kites showed high levels of annual site fidelity to most isolated wetlands (probability ranged from 0?72 to 0?95 per year). 5. We tested the effects of patch size and interpatch distance on movement. Our modelling indicated an effect of both distance and patch size on juveniles' movement (but not adult) when examining movements among fragments. 6. Only a small proportion of kites escaped a regional drought by moving to refugia (wetlands less affected by drought). Many individuals died after the drought. During drought adult survival dropped by 16% while juvenile survival dropped by 86% (possibly because juveniles were less likely to reach refugia). 7. We hypothesize that fragmentation may decrease kite's resistance to drought by restricting exploratory behaviour.

Florida↗

USGS2009

Modeling cape- and ridge-associated marine sand deposits: A focus on the U.S. Atlantic Continental Shelf

Cape- and ridge-associated marine sand deposits, which accumulate on storm-dominated continental shelves that are undergoing Holocene marine transgression, are particularly notable in a segment of the U.S. Atlantic Continental Shelf that extends southward from the east tip of Long Island, N.Y., and eastward from Cape May at the south end of the New Jersey shoreline. These sand deposits commonly contain sand suitable for shore protection in the form of beach nourishment. Increasing demand for marine sand raises questions about both short- and long-term potential supply and the sustainability of beach nourishment with the prospects of accelerating sea-level rise and increasing storm activity. To address these important issues, quantitative assessments of the volume of marine sand resources are needed. Currently, the U.S. Geological Survey is undertaking these assessments through its national Marine Aggregates and Resources Program (URL http://woodshole.er.usgs.gov/project-pages/aggregates/). In this chapter, we present a hypothetical example of a quantitative assessment of cape-and ridge-associated marine sand deposits in the study area, using proven tools of mineral-resource assessment. Applying these tools requires new models that summarize essential data on the quantity and quality of these deposits. Two representative types of model are descriptive models, which consist of a narrative that allows for a consistent recognition of cape-and ridge-associated marine sand deposits, and quantitative models, which consist of empirical statistical distributions that describe significant deposit characteristics, such as volume and grain-size distribution. Variables of the marine sand deposits considered for quantitative modeling in this study include area, thickness, mean grain size, grain sorting, volume, proportion of sand-dominated facies, and spatial density, of which spatial density is particularly helpful in estimating the number of undiscovered deposits within an assessment area. A Monte Carlo simulation that combines the volume of sand-dominated-facies models with estimates of the hypothetical probable number of undiscovered deposits provides a probabilistic approach to estimating marine sand resources within parts of the U.S. Atlantic Continental Shelf and other comparable marine shelves worldwide.

Atlantic Continental Shelf↗

USGS2013

Land Treatment Digital Library

The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey to catalog legacy land treatment information on Bureau of Land Management lands in the western United States. The LTDL can be used by federal managers and scientists for compiling information for data-calls, producing maps, generating reports, and conducting analyses at varying spatial and temporal scales. The LTDL currently houses thousands of treatments from BLM lands across 10 states. Users can browse a map to find information on individual treatments, perform more complex queries to identify a set of treatments, and view graphs of treatment summary statistics.

Data Series↗

USGS2024

Estimating domestic self-supplied water use in Rhode Island, 2014–21

Water withdrawal from private groundwater wells is often unaccounted for in water planning studies, and water from private wells can be a source of exposure to environmental contaminants. The sizes of populations that depend on private wells for domestic water use and the amounts of water that are withdrawn from these wells are generally poorly represented in data collection efforts because of the challenges of locating, metering, or gathering withdrawal information from individual property owners. To address this problem, the U.S. Geological Survey, in cooperation with the Rhode Island Water Resources Board, estimated the volume of water withdrawn from domestic self-supply wells and the populations who use them for the State of Rhode Island at a 30-meter pixel spatial resolution and one-month temporal resolution between July 2014 and June 2021. The number of people reliant on domestic self-supply wells has increased in Rhode Island over the study period; however, the statewide estimate of total water withdrawal has not statistically increased. Withdrawals from private wells are largest in the inland areas of the western part of the State, and the towns of Scituate and Charlestown have the highest estimated withdrawals. Statewide monthly withdrawals ranged from 3.987 million gallons per day in March 2018 to 7.767 million gallons per day in September 2016. The median per capita domestic water use rate was 46.0 gallons per capita per day.

Rhode Island↗