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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 1,063 records · Page 59Linked to original sources
USGS2001

Simulating the impact of human land use change on forest composition in the Great Plains agroecosystems with the Seedscape model

The expansion and contraction of marginal cropland in the Great Plains often involves small forested strips of land that provide important ecological benefits. The effect of human disturbance on these forests is not well known. Because of their unique structure such forests are not well-represented by forest gap models. In this paper, the development, testing and application of a new model known as Seedscape are described. Seedscape is a modification of the JABOWA-II model, and it uses a spatially-explicit landscape to resolve small-scale features of highly fragmented forests in the eastern Great Plains. It was tested and evaluated with observations from two sites, one in Nebraska and a second in eastern Iowa. Seedscape realistically simulates succession at the Nebraska site, but is less successful at the Iowa site. Seedscape was also applied to the Nebraska site to simulate the effect that varying forest corridor widths, in response to the presumed expansion/contraction of adjacent agricultural land, has on succession properties. Results suggest that small differences in widths have negligible effects on forest composition, but large differences in widths may cause statistically-significant changes in the relative importance of some species. We assert that long-term ecological change in human dominated landscapes is not well understood, in part, because of inadequate modeling techniques. Seedscape provides a much-needed tool for assessing the ecological implications of land use change in forests of predominately agricultural landscapes.

Iowa, Nebraska↗
USGS2007

A global search inversion for earthquake kinematic rupture history: Application to the 2000 western Tottori, Japan earthquake

[1] We present a two-stage nonlinear technique to invert strong motions records and geodetic data to retrieve the rupture history of an earthquake on a finite fault. To account for the actual rupture complexity, the fault parameters are spatially variable peak slip velocity, slip direction, rupture time and risetime. The unknown parameters are given at the nodes of the subfaults, whereas the parameters within a subfault are allowed to vary through a bilinear interpolation of the nodal values. The forward modeling is performed with a discrete wave number technique, whose Green's functions include the complete response of the vertically varying Earth structure. During the first stage, an algorithm based on the heat-bath simulated annealing generates an ensemble of models that efficiently sample the good data-fitting regions of parameter space. In the second stage (appraisal), the algorithm performs a statistical analysis of the model ensemble and computes a weighted mean model and its standard deviation. This technique, rather than simply looking at the best model, extracts the most stable features of the earthquake rupture that are consistent with the data and gives an estimate of the variability of each model parameter. We present some synthetic tests to show the effectiveness of the method and its robustness to uncertainty of the adopted crustal model. Finally, we apply this inverse technique to the well recorded 2000 western Tottori, Japan, earthquake ( Mw 6.6); we confirm that the rupture process is characterized by large slip (3-4 m) at very shallow depths but, differently from previous studies, we imaged a new slip patch (2-2.5 m) located deeper, between 14 and 18 km depth.

Tottori↗
USGS2007

Surface-Water Conditions in Georgia, Water Year 2005

INTRODUCTION The U.S. Geological Survey (USGS) Georgia Water Science Center-in cooperation with Federal, State, and local agencies-collected surface-water streamflow, water-quality, and ecological data during the 2005 Water Year (October 1, 2004-September 30, 2005). These data were compiled into layers of an interactive ArcReaderTM published map document (pmf). ArcReaderTM is a product of Environmental Systems Research Institute, Inc (ESRI?). Datasets represented on the interactive map are * continuous daily mean streamflow * continuous daily mean water levels * continuous daily total precipitation * continuous daily water quality (water temperature, specific conductance dissolved oxygen, pH, and turbidity) * noncontinuous peak streamflow * miscellaneous streamflow measurements * lake or reservoir elevation * periodic surface-water quality * periodic ecological data * historical continuous daily mean streamflow discontinued prior to the 2005 water year The map interface provides the ability to identify a station in spatial reference to the political boundaries of the State of Georgia and other features-such as major streams, major roads, and other collection stations. Each station is hyperlinked to a station summary showing seasonal and annual stream characteristics for the current year and for the period of record. For continuous discharge stations, the station summary includes a one page graphical summary page containing five graphs, a station map, and a photograph of the station. The graphs provide a quick overview of the current and period-of-record hydrologic conditions of the station by providing a daily mean discharge graph for the water year, monthly statistics graph for the water year and period of record, an annual mean streamflow graph for the period of record, an annual minimum 7-day average streamflow graph for the period of record, and an annual peak streamflow graph for the period of record. Additionally, data can be accessed through the layer's link to the National Water Inventory System Web (NWISWeb) Interface.

Georgia↗
USGS2016

Modeling the effects of land cover and use on landscape capability for urban ungulate populations

Expanding ungulate populations are causing concerns for wildlife professionals and residents in many urban areas worldwide. Nowhere is the phenomenon more apparent than in the eastern US, where urban white-tailed deer (Odocoileus virginianus) populations are increasing. Most habitat suitability models for deer have been developed in rural areas and across large (>1000 km2) spatial extents. Only recently have we begun to understand the factors that contribute to space use by deer over much smaller spatial extents. In this study, we explore the concepts, terminology, methodology and state-of-the-science in wildlife abundance modeling as applied to overabundant deer populations across heterogeneous urban landscapes. We used classified, high-resolution digital orthoimagery to extract landscape characteristics in several urban areas of upstate New York. In addition, we assessed deer abundance and distribution in 1-km2 blocks across each study area from either aerial surveys or ground-based distance sampling. We recorded the number of detections in each block and used binomial mixture models to explore important relationships between abundance and key landscape features. Finally, we cross-validated statistical models of abundance and compared covariate relationships across study sites. Study areas were characterized along a gradient of urbanization based on the proportions of impervious surfaces and natural vegetation which, based on the best-supported models, also distinguished blocks potentially occupied by deer. Models performed better at identifying occurrence of deer and worse at predicting abundance in cross-validation comparisons. We attribute poor predictive performance to differences in deer population trajectories over time. The proportion of impervious surfaces often yielded better predictions of abundance and occurrence than did the proportion of natural vegetation, which we attribute to a lack of certain land cover classes during cold and snowy winters. Merits and limitations of our approach to habitat suitability modeling are discussed in detail.

Book chapter↗
USGS2020

Units recovery methods in compositional data analysis

Compositional data carry relative information. Hence, their statistical analysis has to be performed on coordinates with respect to a log-ratio basis. Frequently, the modeler is required to back-transform the estimates obtained with the modeling to have them in the original units such as euros, kg or mg/liter. Approaches for recovering original units need to be formally introduced and its properties explored. Here, we formulate and analyze the properties of two procedures: a simple approach consisting of adding a residual part to the composition and an approach based on the use of an auxiliary variable. Both procedures are illustrated using a geochemical data set where the original units are recovered when spatial models are applied.

Natural Resources Research↗
USGS2019

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (>250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, ten time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the 3 time-periods over 12 months (monsoon: Julian days 151-300; winter: Julian days 301-365 plus 1-60; and summer: Julian days 61-150), taking the every 8-day data from Landsat-8 and 7 for the years 2013-2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the 5 agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N=2179) in 5 AEZs. Classification was performed on GEE for each of the 5 AEZs using well-established knowledge-based and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N=1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/

GIScience and Remote Sensing↗
USGS2019

Multi-country willingness to pay for transborder migratory species conservation: A case study of Northern Pintails

Using contingent valuation, we estimated willingness to pay (WTP) in Canada, Mexico, and the United States to protect habitat for Northern Pintails (hereafter pintails), a migratory waterfowl species that provides benefits to and requires habitat in the three countries. Our study contributes to research on spatial subsidies by measuring the value of migratory species habitat. While WTP to protect pintail habitat is highest in the household's own country, there also is substantial WTP to protect pintail habitat in the other two countries. Canadian households' annual WTP is US$12 (all dollar values are in 2016 US dollars) to stabilize the pintail population in Canada, US$4 in Mexico, and US$5 in the U.S. Mexican households would pay US$8 in Mexico, US$5 in the U.S., and US$5 in Canada. U.S. households would pay US$28 in the U.S., US$18 in Canada, and US$16 in Mexico. WTP is statistically significantly higher in all three countries to increase the pintail population. WTP as a percentage of household income is statistically significantly higher for respondents in Mexico. WTP is logically related to explanatory variables such as respondent income, interest in hunting waterfowl, and financial support of wildlife conservation organizations. This study has important implications for conducting economic analyses of habitat issues of transboundary migratory species' conservation and to more effectively and equitably achieve conservation goals.

Ecological Economics↗
USGS2001

Use of thematic mapper imagery to assess water quality, trophic state, and macrophyte distributions in Massachusetts lakes

During the spring and summer of 1996, 1997, and 1998, measurements of phytoplankton- chlorophyll concentration, Secchi disk transparency, and color were made at 97 Massachusetts lakes within 24 hours of Landsat Thematic Mapper imaging of the lakes in an effort to assess water quality and trophic state. Spatial distributions of floating, emergent, and submerged macrophytes were mapped in 49 of the lakes at least once during the 3-year period. The maps were digitized and used to assign pixels in the thematic mapper images to one of four vegetation cover classes-open water, 1-50 percent floating-and-emergent-vegetation cover, 51-100 percent floating-and-emergent-vegetation cover, and submerged vegetation at any density. The field data were collected by teams of U.S. Geological Survey and Massachusetts Department of Environmental Management staff and by 76 volunteers. Side-by-side sampling by U.S. Geological Survey and volunteer field teams resulted in statistically similar chlorophyll determinations, Secchi disk readings, and temperature measurements, but concurrent color determinations were not similar, possibly due to contamination of sample bottles issued to the volunteers.Attempts to develop predictive relations between phytoplankton-chlorophyll concentration, Secchi disk transparency, lake color, dissolved organic carbon, and various combinations of thematic mapper bands 1, 2, 3, and 4 digital numbers were unsuccessful, primarily because of the extremely low concentrations of chlorophyll in the lakes studied, and also because of the highly variable dissolved organic carbon concentrations.Predictive relations were developed between Secchi disk transparency and phytoplankton-chlorophyll concentration, and between color and dissolved organic carbon concentration. Phytoplankton-chlorophyll concentration was inversely correlated with Secchi disk transparency during all three sampling periods. The relations were very similar in 1996 and 1997 and indicated that 62 to 67 percent of the variability in Secchi disk transparency could be explained by the chlorophyll concentration. Analysis of color and dissolved organic carbon concentrations in water samples collected by U.S. Geological Survey field teams in 1996-98 indicated that 91 percent of the variance in color in Massachusetts lakes can be explained by variations in dissolved organic carbon.Areas of open-water, submerged vegetation, and two surface-vegetation-cover classes predicted from Thematic Mapper images acquired in the summer of 1996 closely matched the areas observed in a set of field observations. However, the same analysis applied to a set of data acquired in the summer of 1997 resulted in somewhat less reliable predictions, and an attempt to predict 1996 vegetation-cover areas using the relations developed in the 1997 analysis was unsuccessful.

Water-Resources Investigations Report↗
USGS1999

Relation of arsenic, iron, and manganese in ground water to aquifer type, bedrock lithogeochemistry, and land use in the New England coastal basins

In a study of arsenic concentrations in public-supply wells in the New England Coastal Basins, concentrations at or above 0.005 mg/L (milligrams per liter) were detected in more samples of water from wells completed in bedrock (25 percent of all samples) than in water from wells completed in stratified drift (7.5 percent of all samples). Iron and manganese were detected (at concentrations of 0.05 and 0.03 mg/L, respectively) at approximately the same frequency in water from wells in both types of aquifers. Concentrations of arsenic in public-supply wells drilled in bedrock (in the National Water-Quality Assessment Program New England Coastal Basins study unit) vary with the bedrock lithology. Broad groups of lithogeochemical units generalized from bedrock lithologic units shown on state geologic maps were used in the statistical analyses. Concentrations of arsenic in water from public-supply wells in metasedimentary bedrock units that contain slightly to moderately calcareous and calcsilicate rocks (lithogeochemical group M c ) were significantly higher than the concentrations in five other groups of bedrock units in the study unit. Arsenic was detected, at or above 0.005 mg/L, in water from 44 percent of the wells in the lithogeochemical group M c and in water from less than 28 percent of wells in the five other groups. Additionally, arsenic concentrations in ground water were the lowest in the metasedimentary rocks that are characterized as variably sulfidic (group M s ). Generally, concentrations of arsenic were low in water from bedrock wells in the felsic igneous rocks (group I f ) though locally some bedrock wells in granitic rocks are known to have ground water with high arsenic concentrations, especially in New Hampshire. The concentrations of arsenic in ground water also correlate with land-use data; significantly higher concentrations are found in areas identified as agricultural land use than in undeveloped areas. There is, however, more agricultural land in areas overlying the metasedimentary rocks of lithogeochemical groups M c and the minimally-deformed clastic sediments of group M md than in areas overlying other lithogeochemical groups. This correlation complicates the interpretation of sources of arsenic to ground water in bedrock. A test of this association revealed that relations between arsenic concentrations and the metasedimentary rocks of group M c are not weakened when data associated with agricultural land use is removed; the reverse is true, however, if the data associated with the group M c are removed from the analysis. The occurrence and variability of arsenic in water from bedrock supply wells could be related to several factors. These include (1) the distribution and chemical form of arsenic in soils and rocks that are part of the ground-water-flow system, (2) the characteristics that influence the solubility and transport of arsenic in ground water, (3) the differing degrees of vulnerability of ground-water supplies to surface contamination, and (4) the spatial associations between land use, geology, and ground-water-flow patterns. Strong relations between agricultural land use and the metasedimentary rocks of group M c complicate the interpretation of arsenic source to water in these bedrock aquifers. This is due in part to the past use of arsenical pesticides; additionally, few whole-rock geochemical data are available for the rock types in the lithogeochemical groups of aquifers that contain ground water with elevated concentrations of arsenic. Without such data, identifying specific bedrock types as arsenic sources is not possible. In southern Maine and south-central New Hampshire, and in northern Massachusetts, the few available whole-rock analyses suggest, at least for these local areas, a connection between known bedrock chemistry and ground-water arsenic levels. Although the lithogeochemical group and land-use category variables individually describe much of the variance in the concentrations of arsenic in ground water, the lithogeochemical relation is statistically stronger than the land-use relation. Low concentrations of arsenic in water from bedrock public-supply wells are associated with the metasedimentary rocks of group M s (characterized as variably sulfidic). This association could reflect a variety of factors and suggests that simple dissolution of arsenic-bearing iron phases, such as sulfides, may not explain concentrations of arsenic in water in this bedrock aquifer group. Whole-rock geochemical data and more complete water-chemistry data, as well as studies of historical variation of arsenic concentrations (time-line studies), and site-specific studies, will be critical in addressing the arsenic source issue.

New England coastal basins↗
USGS2025

Automated generation of an urban synthetic elevation checkpoint network across the North Carolina coastline, USA

Lidar and structure from motion-derived digital elevation and surface models have widespread application. Consideration of a topographic model's vertical root mean squared error (RMSEz) and systematic directional bias is important for many of these applications, particularly landscape change detection and measurement. Due to logistic, resource, and time constraints, wide area remotely sensed topographic surveys are not always accompanied by an in situ checkpoint network for validating and characterizing survey error. Here we describe and test a method for automatically generating synthetic elevation checkpoints in bulk across hundreds of kilometers using a publicly available lidar-derived DEM time-series, road vector network, and landcover classification map. Our method produced 6000–10,000 synthetic checkpoints across the developed barrier island coastline of North Carolina. These checkpoints characterized vertical error metrics in a statistically similar way as in situ checkpoints when assessing the vertical accuracy of a contemporary lidar-derived DEM and produced RMSEz metrics an average of 0.018 m from the RMSEz of historical lidar DEMs published with tested accuracy metrics. This new method has the potential to A) lower the cost and time required to validate new remotely sensed topographic surveys by reducing or eliminating the field work associated with in situ checkpoint surveys, B) provide a means of retroactively assessing the absolute vertical accuracy and systematic bias of historical topographic datasets that were not published with tested accuracy metrics, and C) generate reference networks to assess and correct spatially variable patterns of vertical bias in topographic datasets.

North Carolina↗
USGS2010

On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake

Most models of lower crust/mantle viscosity inferred from postearthquake relaxation assume one or two uniform-viscosity layers. A few existing models possess apparently significant radially variable viscosity structure in the shallow mantle (e.g., the upper 200 km), but the resolution of such variations is not clear. We use a geophysical inverse procedure to address the resolving power of inferred shallow mantle viscosity structure using postearthquake relaxation data. We apply this methodology to 9 years of GPS-constrained crustal motions after the 16 October 1999 M = 7.1 Hector Mine earthquake. After application of a differencing method to isolate the postearthquake signal from the “background” crustal velocity field, we find that surface velocities diminish from ∼20 mm/yr in the first few months to ≲2 mm/yr after 2 years. Viscoelastic relaxation of the mantle, with a time-dependent effective viscosity prescribed by a Burgers body, provides a good explanation for the postseismic crustal deformation, capturing both the spatial and temporal pattern. In the context of the Burgers body model (which involves a transient viscosity and steady state viscosity), a resolution analysis based on the singular value decomposition reveals that at most, two constraints on depth-dependent steady state mantle viscosity are provided by the present data set. Uppermost mantle viscosity (depth ≲ 60 km) is moderately resolved, but deeper viscosity structure is poorly resolved. The simplest model that explains the data better than that of uniform steady state mantle viscosity involves a linear gradient in logarithmic viscosity with depth, with a small increase from the Moho to 220 km depth. However, the viscosity increase is not statistically significant. This suggests that the depth-dependent steady state viscosity is not resolvably different from uniformity in the uppermost mantle.

California↗
USGS2020

Identifying areas of degrading and improving groundwater-quality conditions in the State of California, USA, 1974-2014

Areas of improving and degrading groundwater-quality conditions in the State of California were assessed using spatial weighting of a new metric for scoring wells based on constituent concentrations and the direction and magnitude of a trend slope (Sen). Individual well scores were aggregated across 2135 equal-area grid cells covering the entire groundwater resource used for public supply in the state. Spatial weighting allows results to be aggregated locally (well or grid cell), regionally (groundwater basin), provincially, or statewide. Results differentiate degrading (increasing concentration trends) areas with low to moderate concentrations (unimpaired) from degrading areas with moderate to high concentrations (impaired). Results also differentiate improving areas (decreasing concentration trends) in the same manner. Multi-year to decadal groundwater-quality trends were computed from periodic, inorganic water-quality data for 38 constituents collected between 1974 and 2014 for compliance monitoring of nearly 13,000 public-supply wells (PSWs) in the State of California. Mann-Kendall (MK) rank correlations and Sen’s slope estimator were used to detect statistically significant trends for the entire period of recorded data (long-term trend), for the period since 2000 (recent trend), for different pumping seasons (seasonal trend), and for reversals of trends. Statewide, the most frequently detected trends since 2000 were for nitrate (36%), gross alpha/uranium (10%), arsenic (14%), total dissolved solids (TDS) (23%), and the major ions that contribute to TDS (19–28%). The Transverse and Selected Peninsular Ranges (TSPR) and the San Joaquin Valley (SJV) hydrogeologic provinces had the largest percentage of areas with moderate to high nitrate concentrations and groundwater quality trends. Improving nitrate concentrations in parts of the TSPR is associated with long-term managed aquifer recharge that has replaced historical, agriculturally affected groundwater with low-nitrate recharge in parts of the TSPR. This example suggests that application of dilute, excess surface water to agricultural fields during the winter could improve groundwater-quality in the SJV over the long term.

California↗
USGS2022

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire behavior and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns would support better policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. High severity patch simulations was comparable between the coarse and fine resolution vegetation datasets. Improving our ability to simulate burn severity will help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps can support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

California↗
USGS2015

Pore-pressure sensitivities to dynamic strains: observations in active tectonic regions

Triggered seismicity arising from dynamic stresses is often explained by the Mohr-Coulomb failure criterion, where elevated pore pressures reduce the effective strength of faults in fluid-saturated rock. The seismic response of a fluid-rock system naturally depends on its hydro-mechanical properties, but accurately assessing how pore-fluid pressure responds to applied stress over large scales in situ remains a challenging task; hence, spatial variations in response are not well understood, especially around active faults. Here I analyze previously unutilized records of dynamic strain and pore-pressure from regional and teleseismic earthquakes at Plate Boundary Observatory (PBO) stations from 2006 through 2012 to investigate variations in response along the Pacific/North American tectonic plate boundary. I find robust scaling-response coefficients between excess pore pressure and dynamic strain at each station that are spatially correlated: around the San Andreas and San Jacinto fault systems, the response is lowest in regions of the crust undergoing the highest rates of secular shear strain. PBO stations in the Parkfield instrument cluster are at comparable distances to the San Andreas fault (SAF), and spatial variations there follow patterns in dextral creep rates along the fault, with the highest response in the actively creeping section, which is consistent with a narrowing zone of strain accumulation seen in geodetic velocity profiles. At stations in the San Juan Bautista (SJB) and Anza instrument clusters, the response depends non-linearly on the inverse fault-perpendicular distance, with the response decreasing towards the fault; the SJB cluster is at the northern transition from creeping-to-locked behavior along the SAF, where creep rates are at moderate to low levels, and the Anza cluster is around the San Jacinto fault, where to date there have been no statistically significant creep rates observed at the surface. These results suggest that the strength of the pore pressure response in fluid-saturated rock near active faults is controlled by shear strain accumulation associated with tectonic loading, which implies a strong feedback between fault strength and permeability: dynamic triggering susceptibilities may vary in space and also in time.

Journal of Geophysical Research B: Solid Earth↗
USGS2002

Spatio-temporal dynamics of species richness in coastal fish communities

Determining patterns of change in species richness and the processes underlying the dynamics of biodiversity are of key interest within the field of ecology, but few studies have investigated the dynamics of vertebrate communities at a decadal temporal scale. Here, we report findings on the spado-temporal variability in the richness and composition of fish communities along the Norwegian Skagerrak coast having been surveyed for more than half a century. Using statistical models incorporating non-detection and associated sampling variance, we estimate local species richness and changes in species composition allowing us to compute temporal variability in species richness. We tested whether temporal variation could be related to distance to the open sea and to local levels of pollution. Clear differences in mean species richness and temporal variability are observed between fjords that were and were not exposed to the effects of pollution. Altogether this indicates that the fjord is an appropriate scale for studying changes in coastal fish communities in space and time. The year-to-year rates of local extinction and turnover were found to be smaller than spatial differences in community composition. At the regional level, exposure to the open sea plays a homogenizing role, possibly due to coastal currents and advection.

Proceedings of the Royal Society B: Biological Sci↗
USGS2004

Invertebrate egg banks of restored, natural, and drained wetlands in the Prairie Pothole Region of the United States

Analogous to ‘seed banks,’ ‘egg banks’ are important for seasonal succession and maintenance of invertebrate species diversity throughout wet and dry cycles in the prairie pothole region. Further, recruitment of invertebrates from relic egg banks in the sediments and dispersal of eggs into wetlands is believed to be important for reestablishment of invertebrates in recently restored wetlands. Alhough tens-ofthousands of wetlands have been restored in the prairie pothole region of the United States, studies have not been conducted to evaluate the recovery of invertebrate egg banks in restored wetlands. We used taxon richness and abundance as indicators of potential egg bank recovery and compared these parameters in restored wetlands to those of non-drained and drained wetlands with a history of cultivation and also to reference wetlands with no history of cultivation. We found few significant differences among wetland categories within three physiographic regions (Glaciated Plains, Missouri Coteau, and Prairie Coteau). Most statistical comparisons indicated that restored wetlands had invertebrate egg banks similar to reference, nondrained, and drained wetlands. The one exception was drained seasonal wetlands in the Glaciated Plains, which had significantly lower taxon richness and invertebrate abundance than the other wetland categories. Trends did suggest that invertebrate egg bank taxon richness and abundance are increasing in restored seasonal wetlands relative to their drained analogues, whereas a similar trend was not observed for restored semi-permanent wetlands. Although recovery was not related to years since restoration, comparisons of restored wetlands with reference wetlands suggest that recovery potential may be inversely related to the extent of wetland drainage and intensive agriculture that varies spatially in the prairie pothole region. Our research suggests that periodic drawdowns of semi-permanent restored wetlands may be needed to promote production and development of invertebrate egg banks. Inoculation of restored wetlands may also be needed in areas where extensive wetland drainage has resulted in fewer wetland habitats to provide sources of passively dispersed eggs to newly restored wetlands.

Iowa, Minnesota, Montana, North Dakota, South Dako↗
USGS2017

Is “morphodynamic equilibrium” an oxymoron?

Morphodynamic equilibrium is a widely adopted yet elusive concept in the field of geomorphology of coasts, rivers and estuaries. Based on the Exner equation, an expression of mass conservation of sediment, we distinguish three types of equilibrium defined as static and dynamic, of which two different types exist. Other expressions such as statistical and quasi-equilibrium which do not strictly satisfy the Exner conditions are also acknowledged for their practical use. The choice of a temporal scale is imperative to analyse the type of equilibrium. We discuss the difference between morphodynamic equilibrium in the “real world” (nature) and the “virtual world” (model). Modelling studies rely on simplifications of the real world and lead to understanding of process interactions. A variety of factors affect the use of virtual-world predictions in the real world (e.g., variability in environmental drivers and variability in the setting) so that the concept of morphodynamic equilibrium should be mathematically unequivocal in the virtual world and interpreted over the appropriate spatial and temporal scale in the real world. We draw examples from estuarine settings which are subject to various governing factors which broadly include hydrodynamics, sedimentology and landscape setting. Following the traditional “tide-wave-river” ternary diagram, we summarize studies to date that explore the “virtual world”, discuss the type of equilibrium reached and how it relates to the real world.

Earth-Science Reviews↗
USGS2023

Estimating lentic recreational fisheries catch and effort across the United States

Recreational fisheries represent a socially, ecologically, and economically significant component of global fisheries. The U.S. Inland Creel and Angler Survey Catalog (CreelCat) database includes inland recreational fisheries survey data across the United States to facilitate large-scale analyses. However, because survey methods differ, a statistical method capable of integrating these surveys is necessary to assess patterns and relationships across regions. Here, we developed a hierarchical generalized linear mixed modeling approach to estimate the relationship between daily recreational fisheries catch and effort based on waterbody, socio-economic, and ecological covariates. We applied this approach to CreelCat data on lentic waterbodies and found that recreational fisheries catch and effort were non-linearly related (i.e., catch per unit of effort declined as effort increased), where effort varied regionally and by waterbody area, median county age, and distance to nearest primary road. This modeling approach could be used to inform data-poor regions or waterbodies, make comparisons across spatial scales, and, with the inclusion of socio-economic and ecological factors, inform management techniques in an era of shifting demographics and landscapes.

Fisheries Management and Ecology↗