Search USGSSearch

SEARCH · Search USGS

Results for “Data Science in Science”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54Linked to original sources

Fault fictions: Systematic biases in the conceptualization of fault-zone architecture

Mental models are a human's internal representation of the real world and have an important role in the way we understand and reason about uncertainties, explore potential options and make decisions. Mental models have not yet received much attention in geosciences, yet systematic biases can affect any geological investigation: from how the problem is conceived, through selection of appropriate hypotheses and data collection/processing methods, to the conceptualization and communication of results. We draw on findings from cognitive science and system dynamics, with knowledge and experiences of field geology, to consider the limitations and biases presented by mental models in geoscience, and their effect on predictions of the physical properties of faults in particular. We highlight biases specific to geological investigations and propose strategies for debiasing. Doing so will enhance how multiple data sources can be brought together, and minimize controllable geological uncertainty to develop more robust geological models. Critically, there is a need for standardized procedures that guard against biases, permitting data from multiple studies to be combined and communication of assumptions to be made. While we use faults to illustrate potential biases in mental models and the implications of these biases, our findings can be applied across the geosciences.

Special Publications

Sediment data collected in 2012 from the northern Chandeleur Islands, Louisiana

As part of the Barrier Island Evolution Research project, scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center collected sediment samples from the northern Chandeleur Islands in March and September 2012. The overall objective of this project, which integrates geophysical (bathymetric, seismic, and topographic) and sedimentologic data, is to better understand the depositional and erosional processes that drive the morphologic evolution of barrier islands over annual to interannual timescales (1 to 5 years). Between June 2010 and April 2011, in response to the Deepwater Horizon oil spill, the State of Louisiana constructed a sand berm extending more than 14 kilometers along the northern Chandeleur Islands platform. The construction of the berm provided a unique opportunity to investigate how this new sediment source will interact with and affect the morphologic evolution of the barrier-island system. Data collected from this study will be used to describe differences in the physical characteristics and spatial distribution of sediments both along the axis of the berm and also along transects across the berm and onto the adjacent barrier island. Comparison of these data with data from subsequent sampling efforts will provide information about sediment interactions and movement between the berm and the natural island platform, improving our understanding of short-term morphologic change and processes in this barrier-island system. This data series serves as an archive of sediment data collected in March and September 2012 from the Chandeleur Islands sand berm and adjacent barrier-island environments. Data products include descriptive core logs, core photographs and x-radiographs, results of sediment grain-size analyses, sample location maps, and Geographic Information System data files with accompanying formal Federal Geographic Data Committee metadata.

Louisiana

Water-quality, bed-sediment, and biological data, for streams in the upper Prickly Pear Creek watershed, Montana, 2001

The upper Prickly Pear Creek watershed encompasses the upstream 15 miles of Prickly Pear Creek, south of Helena, Montana (fig. 1). The headwaters of Prickly Pear Creek and its tributaries (Beavertown Creek, Clancy Creek, Dutchman Creek, Golconda Creek, Lump Gulch, Spring Creek, and Warm Springs Creek) are primarily in the Helena National Forest, whereas the central part of the watershed primarily is within either Bureau of Land Management (BLM) or privately owned property. Three mining districts are present in the upper Prickly Pear Creek watershed: Alhambra, Clancy, and Colorado. Numerous prospects, adits, tailings piles, mills, dredge piles, and mines (mostly inactive) are located throughout the watershed. These districts contain polymetallic (Ag, Au, Cu, Pb, Zn) vein deposits and precious-metal (Au-Ag) vein and disseminated deposits that were exploited beginning in the 1860’s. Placer Au deposits in the major streams were extensively mined in the late 1800’s and early 1900’s. As part of a cooperative effort with Federal land management agencies, the U.S. Geological Survey (USGS) is currently using an integrated approach to investigate two mining impacted watersheds in the western United States (the Animas River in Colorado and the Boulder River in Montana). These studies provide the USDA Forest Service and BLM scientific data for implementing informed land-management decisions regarding cleanup of abandoned mine lands within each watershed. A similar integrated-science approach will be used to characterize the upper Prickly Pear Creek watershed with respect to water and streambed sediment chemistry, aquatic biota, and geologic framework. This integrated database presents data that will be used to identify important pathways of metals movement and biological impacts, thereby guiding resource management decisions of land-managers in several publications that are in preparation. Watershed-level characterization in terms of water quality, streambed sediment chemistry, and fish health will facilitate determinations of whether removal of contaminated materials or other cleanup activities are necessary, planning of short- and long-term restoration efforts, and development of a monitoring plan to document cleanup effectiveness.

Montana

Geographic information system datasets of regolith-thickness data, regolith-thickness contours, raster-based regolith thickness, and aquifer-test and specific-capacity data for the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado

These datasets were compiled in support of U.S. Geological Survey Scientific-Investigations Report 2010-5082-Hydrogeology and Steady-State Numerical Simulation of Groundwater Flow in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. The datasets were developed by the U.S. Geological Survey in cooperation with the Lost Creek Ground Water Management District and the Colorado Geological Survey. The four datasets are described as follows and methods used to develop the datasets are further described in Scientific-Investigations Report 2010-5082: (1) ds507_regolith_data: This point dataset contains geologic information concerning regolith (unconsolidated sediment) thickness and top-of-bedrock altitude at selected well and test-hole locations in and near the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Data were compiled from published reports, consultant reports, and from lithologic logs of wells and test holes on file with the U.S. Geological Survey Colorado Water Science Center and the Colorado Division of Water Resources. (2) ds507_regthick_contours: This dataset consists of contours showing generalized lines of equal regolith thickness overlying bedrock in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Regolith thickness was contoured manually on the basis of information provided in the dataset ds507_regolith_data. (3) ds507_regthick_grid: This dataset consists of raster-based generalized thickness of regolith overlying bedrock in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. Regolith thickness in this dataset was derived from contours presented in the dataset ds507_regthick_contours. (4) ds507_welltest_data: This point dataset contains estimates of aquifer transmissivity and hydraulic conductivity at selected well locations in the Lost Creek Designated Ground Water Basin, Weld, Adams, and Arapahoe Counties, Colorado. This dataset also contains hydrologic information used to estimate transmissivity from specific capacity at selected well locations. Data were compiled from published reports, consultant reports, and from well-test records on file with the U.S. Geological Survey Colorado Water Science Center and the Colorado Division of Water Resources.

Data Series

U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward

This “U.S. Geological Survey Pollinator Science Strategy, 2025–35—A Review and Look Forward” (“Pollinator Science Strategy”) describes the science vision of the U.S. Geological Survey (USGS) to support management, conservation, and policy decisions on animal pollinators and their habitats. As the science arm of the Department of the Interior, the USGS has a primary role in providing scientific information to natural resource managers and policymakers across the United States. This “Pollinator Science Strategy” was drafted by a team of USGS pollinator researchers and was further developed through feedback from Federal, State, Tribal, nongovernmental organizations, and industry partners. This “Pollinator Science Strategy” highlights the USGS’s role in the research to promote healthy pollinator populations and address partner information gaps so they can make more informed management decisions. By outlining the importance of USGS science in addressing the information needs of other agencies, organizations, and the public, the “Pollinator Science Strategy” reaffirms the USGS’s commitment to pollinator research and showcases our research priorities for 2025–35. With more than 300 research centers nationally, the USGS is equipped to address pollinator science across scales of complexity and geographic range. USGS pollinator science is organized according to the following five thematic areas: Assessing species ecology, distributions, and natural history requirements. Tracking species status and trends. Understanding species threats and stressors. Informing restoration and management actions. Developing novel methods for improving pollinator research, monitoring, and population outcomes that can benefit our Nation. Our pollinator information products and associated data are made widely available to the public to ensure scientific transparency and accessibility. This “Pollinator Science Strategy” concludes with several research goals that the USGS will work towards from 2025 to 2035, representing our vision for USGS science. These research goals include synthesizing and modernizing the latest information on pollinator threats, developing research that assists managers with habitat design and restoration, providing training to partners on native bee identification and monitoring design, and developing new technologies for assessing the status and trends of our nation’s pollinators.

Circular

Collection and analysis of high-resolution elevation data for the Lincoln Lidar Project, Lincoln, Nebraska, 2004

The Lincoln Lidar Project was a partnership developed between the U.S. Geological Survey National Center for Earth Resources Observations and Science (EROS), Lancaster County and the city of Lincoln, Nebraska. This project demonstrated a successful planning, collection, analysis and integration of high-resolution elevation information using Light Detection and Ranging, (Lidar) data. This report describes the partnership developed to collect local Lidar data and transform the data into information useable at local to national levels. This report specifically describes project planning, quality assurance, processing, transforming raw Lidar points to useable data layers, and visualizing and disseminating the raw and final products.

Nebraska

Automated calculation of surface energy fluxes with high-frequency lake buoy data

Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.

Environmental Modelling and Software

Ecology and space: A case study in mapping harmful invasive species

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass ( Bromus tectorum ) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Book chapter

Science in the Public Sphere: Greater Sage-grouse Conservation Planning from a Transdisciplinary Perspective

Integration of scientific data and adaptive management techniques is critical to the success of species conservation, however, there are uncertainties about effective methods of knowledge exchange between scientists and decisionmakers. The conservation planning and implementation process for Greater Sage-grouse (Centrocercus urophasianus; ) in the Mono Basin, Calif. region, was used as a case study to observe the exchange of scientific information among stakeholders with differing perspectives; resource manager, scientist, public official, rancher, and others. The collaborative development of a risk-simulation model was explored as a tool to transfer knowledge between stakeholders and inform conservation planning and management decisions. Observations compiled using a transdisciplinary approach were used to compare the exchange of information during the collaborative model development and more traditional interactions such as scientist-led presentations at stakeholder meetings. Lack of congruence around knowledge needs and prioritization led to insufficient commitment to completely implement the risk-simulation model. Ethnographic analysis of the case study suggests that further application of epistemic community theory, which posits a strong boundary condition on knowledge transfer, could help support application of risk simulation models in conservation-planning efforts within similarly complex social and bureaucratic landscapes.

Open-File Report

Science to support the understanding of Ohio's water resources

Ohio’s water resources support a complex web of human activities and nature—clean and abundant water is needed for drinking, recreation, farming, and industry, as well as for fish and wildlife needs. The distribution of rainfall can cause floods and droughts, which affects streamflow, groundwater, water availability, water quality, recreation, and aquatic habitats. Ohio is bordered by the Ohio River and Lake Erie and has over 44,000 miles of streams and more than 60,000 lakes and ponds (State of Ohio, 1994). Nearly all the rural population obtain drinking water from groundwater sources. The U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as universities, to furnish decisionmakers, policymakers, USGS scientists, and the general public with reliable scientific information and tools to assist them in management, stewardship, and use of Ohio’s natural resources. The diversity of scientific expertise among USGS personnel enables them to carry out large- and small-scale multidisciplinary studies. The USGS is unique among government organizations because it has neither regulatory nor developmental authority—its sole product is reliable, impartial, credible, relevant, and timely scientific information, equally accessible and available to everyone. The USGS Ohio Water Science Center provides reliable hydrologic and water-related ecological information to aid in the understanding of use and management of the Nation’s water resources, in general, and Ohio’s water resources, in particular. This fact sheet provides an overview of current (2012) or recently completed USGS studies and data activities pertaining to water resources in Ohio. More information regarding projects of the USGS Ohio Water Science Center is available at http://oh.water.usgs.gov/.

Ohio

Archive of digital boomer subbottom data collected during USGS cruises 99FGS01 and 99FGS02 offshore southeast and southwest Florida, July and November, 1999

In July (19 - 26) and November (17 - 18) of 1999, the USGS, in cooperation with the Florida Geological Survey (FGS), conducted two geophysical surveys in: (1) the Atlantic Ocean offshore of Florida's east coast from Orchid to Jupiter, FL, and (2) the Gulf of Mexico offshore of Venice, FL. This report serves as an archive of unprocessed digital boomer subbottom data, trackline maps, navigation files, GIS files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (showing a relative increase in signal amplitude) digital images of the subbottom profiles are also provided. The USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, identifiers 99FGS01 and 99FGS02 refer to field data collected in 1999 for cooperative work with the FGS. The numbers 01 and 02 indicate the data were collected during the first and second field activities for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity identification (ID).

Florida

U.S. Geological Survey Activities Related to American Indians and Alaska Natives Fiscal Year 2002

Information is a resource for Native American governments, communities, organizations, and people. The U.S. Geological Survey (USGS) provides technical expertise, reports, and other impartial information sources that benefit Native Americans interested in subsistence issues, water, land use, and the health of many parts of the environment. Native self-sufficiency, economic development, and conservation are cultivated through Native decisions informed with USGS data and analyses. The USGS works in cooperation with American Indian and Alaska Native governments, conducting research on water and mineral resources, animals and plants of environmental, economic, or subsistence importance, natural hazards, and geologic resources. Digital data on cartography, mineral resources, streamflow, biota, and other topics are available to American Indian and Alaska Native individuals and institutions. The USGS recognizes the need to learn from and share knowledge with Native peoples. This report describes most of the activities that the USGS conducted with American Indian and Alaska Native governments, educational institutions, and individuals during Federal Fiscal Year 2002. Some of these USGS activities were carried out in concert with the Bureau of Indian Affairs (BIA). Others were conducted by Tribes, Tribal organizations, professional societies, and the USGS. A growing number of Tribal governments, educational institutions, and other Tribal organizations have begun using geographic information systems and other digital technologies in recent years. As Tribes become more interested in and more adept at managing digital information, they are seeking relevant data from the USGS more frequently. Using digital technologies provides Tribal governments with additional means of managing lands and resources for the benefit of current and future generations. The USGS recognizes the need to make its information available to Tribal governments, and to work with those governments and other institutions to advance data management capabilities. The USGS also recognizes that Tribal institutions have varying needs, interests, and capacities. The USGS strives to be sensitive to the unique circumstances of each of these institutions while supporting their self-driven evolution. The USGS is responding to these needs by increasing the transfer of scientific information to American Indian and Alaska Native governments and by training employees of those governments to conduct scientific studies and improve scientific data management. The USGS is also encouraging American Indians and Alaska Natives to pursue careers in science and seeking ways to hire Indian and Native students. By identifying, improving, and disseminating information about available hiring mechanisms, the USGS is working to make hiring such students easier, and, therefore, more likely, for USGS managers. The U.S. Geological Survey is the Federal science bureau within the Department of the Interior (DoI). The USGS is non-regulatory and is not a significant manager of Federal or Trust lands or assets. However, as described in this report, there are several types of USGS activities that involve American Indians, Alaska Natives, and their lands. One type of activity is the course of formal studies, conducted through existing USGS programs, that involves collection of specific types of data as well as investigative and research projects. These projects typically last 2 or 3 years, although a few are parts of longer-term activities. Some projects are funded through cooperative agreements, from monies provided to the USGS by individual Tribal governments, or by the BIA. The USGS provides matching funds for cooperative projects. These formal projects may also receive funding from the U.S. Environmental Protection Agency, the Indian Health Service (part of the Department of Health and Human Services), or other Federal agencies. The USGS routinely works with its sister bureaus in the Department of the Interior to provide the scientific information and expertise needed to meet the Department's science priorities. Within this context, the USGS and the BIA are cooperating to use USGS information resources to benefit American Indian and Alaska Native peoples and their lands. The second type of USGS activity is less formal, based on initiatives designed and conducted by USGS employees. Frequently involving educational activities, these endeavors are prompted by employee interests, often as collateral issues, that result from one or more USGS employees identifying and responding to an observed need. In these activities, USGS employees help fulfill a mission of the USGS--to prove scientific relevance--while helping their fellow citizens. Increasingly, some of the educational activities are becoming parts of formal USGS projects. USGS employees have also taken the initiative in assisting American Indians and Alaska Natives through participation in several organizations that were created to foster awareness of science among Native peoples and to help build support and communication networks. One such group is the American Indian Science and Engineering Society (AISES). This group sponsors an annual national meeting in which USGS employees participate. USGS employees join this organization on a voluntary basis, bringing the benefits of this expanded network to the USGS, as many employees do with other professional organizations. Each part of the USGS has identified an American Indian/Alaska Native liaison. The USGS has a regional organizational structure, with Western, Central, and Eastern Regions. The regions work in concert with specific scientific disciplines to conduct the scientific mission of the USGS. The regional structure is intended to bring us closer to our customers; we hope that Native Americans and Alaska Natives will use the contacts listed at the end of this report.

Report

Science to support the understanding of Ohio's water resources, 2014-15

Ohio’s water resources support a complex web of human activities and nature—clean and abundant water is needed for drinking, recreation, farming, and industry, as well as for fish and wildlife needs. Although rainfall in normal years can support these activities and needs, occasional floods and droughts can disrupt streamflow, groundwater, water availability, water quality, recreation, and aquatic habitats. Ohio is bordered by the Ohio River and Lake Erie; it has over 44,000 miles of streams and more than 60,000 lakes and ponds. Nearly all the rural population obtain drinking water from groundwater sources. The U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as universities, to furnish decision makers, policy makers, USGS scientists, and the general public with reliable scientific information and tools to assist them in management, stewardship, and use of Ohio’s natural resources. The diversity of scientific expertise among USGS personnel enables them to carry out large- and small-scale multidisciplinary studies. The USGS is unique among government organizations because it has neither regulatory nor developmental authority—its sole product is impartial, credible, relevant, and timely scientific information, equally accessible and available to everyone. The USGS Ohio Water Science Center provides reliable hydrologic and water-related ecological information to aid in the understanding of the use and management of the Nation’s water resources, in general, and Ohio’s water resources, in particular. This fact sheet provides an overview of current (2014) or recently completed USGS studies and data activities pertaining to water resources in Ohio. More information regarding projects of the USGS Ohio Water Science Center is available at http://oh.water.usgs.gov/ .

Ohio

Science to support the understanding of Ohio's water resources, 2016-17

Ohio’s water resources support a complex web of human activities and nature—clean and abundant water is needed for drinking, recreation, farming, and industry, as well as for fish and wildlife needs. Although rainfall in normal years can support these activities and needs, occasional floods and droughts can disrupt streamflow, groundwater, water availability, water quality, recreation, and aquatic habitats. Ohio is bordered by the Ohio River and Lake Erie; it has over 44,000 miles of streams and more than 60,000 lakes and ponds (State of Ohio, 1994). Nearly all of the rural population obtains drinking water from groundwater sources. The U.S. Geological Survey (USGS) works in cooperation with local, State, and other Federal agencies, as well as universities, to furnish decisionmakers, policy makers, USGS scientists, and the general public with reliable scientific information and tools to assist them in management, stewardship, and use of Ohio’s natural resources. The diversity of scientific expertise among USGS personnel enables them to carry out large- and small-scale multidisciplinary studies. The USGS is unique among government organizations because it has neither regulatory nor developmental authority—its sole product is impartial, credible, relevant, and timely scientific information, equally accessible and available to everyone. The USGS Ohio Water Science Center provides reliable hydrologic and water-related ecological information to aid in the understanding of the use and management of the Nation’s water resources, in general, and Ohio’s water resources, in particular. This fact sheet provides an overview of current (2016) or recently completed USGS studies and data activities pertaining to water resources in Ohio. More information regarding projects of the USGS Ohio Water Science Center is available at http://oh.water.usgs.gov/ .

Ohio

Need and vision for global medium-resolution Landsat and Sentinel-2 data products

Global changes in climate and land use are threatening natural ecosystems, biodiversity, and the ecosystem services people rely on. This is why it is necessary to track and monitor spatiotemporal change at a level of detail that can inform science, management, and policy development. The current constellation of multiple Landsat and Sentinel-2 satellites collecting imagery at predominantly ≤ "> ≤ 30-m spatial resolution affords an opportunity for the generation of global medium- resolution products every few days. Our goal is to both identify the information needs and provide direction towards the generation of a suite of global, high-level, systematically-generated, medium-resolution products designed for both management and science. Our vision builds on the success of the NASA MODIS/VIIRS product suite, while recognizing the unique strengths of medium-resolution satellite data given their higher spatial resolution and longer time series. We propose a suite of 13 essential products that enable the characterization of the current state and changes in the biosphere, cryosphere, and hydrosphere, and would fill information needs identified by the Committee on Earth Observation Satellites for the Global Climate Observing System and the Global Terrestrial Observing System, by the National Research Council of the US National Academies in the decadal survey, and by others. These products are: land cover, land cover change, burned area, forest loss, vegetation indices, phenology, dynamic habitat indices, albedo, land surface temperature, snow cover, ice extent, surface water extent, and evapotranspiration. Furthermore, we provide a list of desirable products poised for addition to the essential products (e.g., crop type, emissivity, and ice sheet velocity). Lastly, we suggest aspirational products requiring further algorithm development (e.g., forest structure and crop yield). For the identified essential products, algorithms are in place, making it feasible to begin generating products systematically. These products should be accompanied by quality and accuracy assessments undertaken following consensus protocols. Five decades after the first Landsat satellite, and two decades after the MODIS products were first produced, it is time now for readily available, standardized, and consistent high-level products built upon medium-resolution imagery, thereby fulfilling the promise and the vision that inspired the Landsat program since its inception.

Remote Sensing of Environment

From satellites to frogs: Quantifying ecohydrological change, drought mitigation, and population demography in desert meadows

Increasing frequency and severity of droughts have motivated natural resource managers to mitigate harmful ecological and hydrological effects of drought, but drought mitigation is an emerging science and evaluating its effectiveness is difficult. We examined ecohydrological responses of drought mitigation actions aimed at conserving populations of the Columbia spotted frog ( Rana luteiventris ) in a semi-arid valley in Nevada, USA. Abundance of this rare frog had declined precipitously after multiple droughts. Mitigation included excavating ponds to increase available surface water and installing earthen dams to raise water tables. We assessed responses of riparian vegetation to mitigation using a 30-year time series of satellite-derived Normalized Difference Vegetation Index (NDVI) and gridded weather data. We then analyzed a 23-year mark-recapture dataset to evaluate the effects of drought mitigation and NDVI on the probability of frog survival and rates of recruitment. After accounting for interannual precipitation variability, we found that NDVI increased significantly from before to after drought mitigation, suggesting that mitigation influenced the hydrology and vegetation of the meadows. Frog survival increased with NDVI, but mitigation had a stronger effect than NDVI suggesting that excavated mitigation ponds were particularly important for frog survival during drought. In contrast, frog recruitment was associated with NDVI more than mitigation, but only in meadows where NDVI was dependent on precipitation. At meadows with available groundwater, recruitment was associated with mitigation ponds. These findings suggest that mitigation ponds are critical for juvenile frogs to recruit into the adult population, but recruitment can also be increased by raising water tables in meadows lacking groundwater sources. Lagged recruitment (i.e., effects on larvae and juveniles) was negatively associated with NDVI. This study illustrates the ecohydrological complexity of drought mitigation and demonstrates novel ways to assess the effectiveness of drought mitigation using time series of readily available satellite imagery and organismal data.

Nevada

Simultaneous autoregressive (SAR) model

Simultaneous autoregressive (SAR) models are useful for accommodating various forms of dependence among data that have discrete support in a space of interest. These models are often specified hierarchically as mixed-effects regression models with first-moment structure controlled by a conventional linear regression term and second-moment structure induced by correlated random effects. In their general form, SAR models resemble conditional autoregressive (CAR) models, and can be made equivalent but are often parameterized differently. Importantly, SAR models can be specified by simultaneously regressing a discrete spatial process on itself. Thus, they allow one to construct statistical models for processes with directional graphical properties that pertain to data generating mechanisms. Most commonly SAR models have been used to account for structure among data with areal spatial support in applications involving ecology, epidemiology, sociology, and environmental science.

Book chapter

Assessment experimental semivariogram uncertainty in the presence of a polynomial drift

The semivariogram, which measures the spatial variability between experimental data, is generally used as a structural input in all two-point geostatistical procedures. However, in most geoscience applications, experimental semivariograms are usually computed from a limited number of sparsely spaced measurements, which results in uncertainty associated with the semivariance values estimated for a specified number of lags. More importantly, considering a spatial variable modelled by a nonstationary random field, uncertainty is not only in the experimental semivariogram of the residuals, but also in the coefficients of the drift model estimated from the available experimental data. Therefore, when assessing the reliability of an experimental semivariogram (or estimated semivariances) in the nonstationary case, both aforementioned uncertainties should be taken into account. The aim of this paper is to extend the “Generalised Bootstrap” procedure to the nonstationary model by propagating the uncertainty associated with the estimated drift coefficients into the uncertainty in the experimental semivariogram of the residuals. The proposed methodology is demonstrated in a case study using abundant geophysical measurements characterised by a nonstationary random function. Two scenarios are evaluated in the case study: (1) it is assumed that the drift coefficients can be estimated without any uncertainty, and (2) uncertainty of the drift coefficients is taken into account. We have explained the methodology that allows to assess the uncertainty of the semivariogram lag estimates in the presence of the drift in the mean. Considering the second scenario, uncertainty is obviously larger than the case where uncertainty of the drift in the mean is ignored. This evaluation should be considered in applications where the data is often rather limited, such as subsurface hydrology (i.e. porosity, transmissivity), soil science (i.e. heavy metal content, soil moisture) and mining (i.e. scoping or pre-feasibility stage of the project). In fact, modern geostatistics should provide not only the semivariogram estimates but also estimation of its uncertainty.

Natural Resources Research