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At least 127 records · Page 7Linked to original sources
USGS2013

Landscape consequences of natural gas extraction in Fayette and Lycoming Counties, Pennsylvania, 2004–2010

Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Fayette County and Lycoming County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.

Pennsylvania↗
USGS2013

Landscape consequences of natural gas extraction in Somerset and Westmoreland Counties, Pennsylvania,2004--2010

Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Somerset County and Westmoreland County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.

Pennsylvania↗
USGS2013

Landscape consequences of natural gas extraction in Beaver and Butler Counties, Pennsylvania, 2004-2010

Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Beaver County and Butler County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.

Pennsylvania↗
USGS2013

Landscape consequences of natural gas extraction in Lackawanna and Wayne Counties, Pennsylvania, 2004-2010

Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Lackawanna County and Wayne County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.

Pennsylvania↗
USGS2013

Landscape consequences of natural gas extraction in Sullivan and Wyoming Counties, Pennsylvania, 2004–2010

Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Sullivan County and Wyoming County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.

Pennsylvania↗
USGS2013

Landscape consequences of natural gas extraction in Armstrong and Indiana Counties, Pennsylvania, 2004–2010

Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Armstrong County and Indiana County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.

Pennsylvania↗
USGS2016

Estimating natural monthly streamflows in California and the likelihood of anthropogenic modification

Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.

California↗
USGS2012

Analysis of annual dissolved-solids loading from selected natural and irrigated catchments in the Upper Colorado River Basin, 1974-2003

Dissolved-solids loading from 17 natural catchments and 14 irrigated catchments in the Upper Colorado River Basin was examined for the period from 1974 through 2003. In general, dissolved-solids loading increased and decreased concurrently in natural and irrigated catchments but at different magnitudes. Annually, the magnitude of loading in natural catchments changed about 10 percent more, on average, than in irrigated catchments. Measures of variability, or spread, indicate that natural catchments had 35 percent greater annual variability in loading than irrigated catchments. Precipitation and dissolved-solids loads were positively correlated in natural catchments, and a weak positive correlation was determined for irrigated catchments. A weak negative correlation between temperature and dissolved-solids load was determined for both natural and irrigated catchments. In irrigated catchments, the dissolved-solids load response to an above-average precipitation period from 1982 through 1987 generally lagged behind that in the natural catchments. On average, irrigated catchments with reservoir storage had the largest normalized maximum annual loads during the wet period.

Arizona, Colorado, New Mexico, Utah, Wyoming↗
USGS1997

Review of selected features of the natural system model, and suggestions for applications in south Florida

A study was conducted to review selected features of the Natural System Model, version 4.3. The Natural System Model is a regional-scale model that uses recent climatic data and estimates of historic vegetation and topography to simulate pre-canal-drainage hydrologic response in south Florida. Equations used to represent the hydrologic system and the numerical solution of these equations in the model were documented and reviewed. Convergence testing was performed using 1965 input data, and selected other aspects of the model were evaluated. Some conclusions from the evaluation of the Natural System Model include the following observations. Simulations were generally insensitive to the temporal resolution used in the model. However, reduction of the computational cell size from 2-mile by 2-mile to 2/3-mile by 2/3-mile resulted in a decrease in spatial mean ponding depths for October of 0.35 foot for a 3-hour time step. Review of the computer code indicated that there is no limit on the amount of water that can be transferred from the river system to the overland flow system, on the amount of seepage from the river to the ground-water system, on evaporation from the river system, or on evapotranspiration from the overland-flow system. Oscillations of 0.2 foot or less in simulated river stage were identified and attributed to a volume limiting function which is applied in solution of the overland-flow equations. The computation of the resistance coefficient is not consistent with the computation of overland-flow velocity. Ground-water boundary conditions do not always ensure a no-flow condition at the boundary. These inconsistencies had varying degrees of effects on model simulations, and it is likely that simulations longer than 1 year are needed to fully identify effects. However, inconsistencies in model formulations should not be ignored, even if the effects of such errors on model results appear to be small or have not been clearly defined. The Natural System Model can be a very useful tool for estimating pre-drainage hydrologic response in south Florida. The model includes all of the important physical processes needed to simulate a water balance. With a few exceptions, these hydrologic processes are represented in a reasonable manner using empirical, semiempirical, and mechanistic relations. The data sets that have been assembled to represent physical features, and hydrologic and meteorological conditions are quite extensive in their scope. Some suggestions for model application were made. Simulation results from the Natural System Model need to be interpreted on a regional basis, rather than cell by cell. The available evidence suggests that simulated water levels should be interpreted with about a plus or minus 1 foot uncertainty. It is probably not appropriate to use the Natural System Model to estimate pre-drainage discharges (as opposed to hydroperiods and water levels) at a particular location or across a set of adjacent computational cells. All simulated results for computational cells within about 10 miles of the model boundaries have a higher degree of uncertainty than results for the interior of the model domain. It is most appropriate to interpret the Natural System Model simulation results in connection with other available information. Stronger linkages between hydrologic inputs to the Everglades and the ecological response of the system would enhance restoration efforts.

Florida↗
USGS1998

Water quality in the vicinity of Mosquito Creek Lake, Trumbull County, Ohio, in relation to the chemistry of locally occurring oil, natural gas, and brine

Environmental samples collected in the Mosquito Creek Lake area were used to characterize water quality in relation to the chemistry of locally occurring oil, natural gas, and brine and to establish baseline water quality. Mosquito Creek Lake (a manmade reservoir) and the shallow bedrock aquifers near the lake are major sources of potable water in central Trumbull County. The city of Warren relies on the lake as a sole source of potable water. Some of the lake bottom may be in direct hydraulic connection with the underlying aquifers. The city of Cortland, along the southeastern shore of the lake, relies on the Cussewago Sandstone aquifer as a sole source of potable water. This aquifer subcrops beneath the glacio-fluvial sediments that underlie the lake. Nearly all residential homes around the lake, with the exception of homes in the city of Cortland, rely on domestic supply wells as a source of potable water. Oil and natural gas exploration and production have been ongoing in the Mosquito Creek Lakearea since the discovery of the historic Mecca Oil Pool in the Mississippian Berea and Cussewago Sandstones in 1860. Since the late 1970' s, the major drilling objective and zone of production is the Lower Silurian Clinton sandstone. The oil and natural gas resources of the Mosquito Creek Lake area, including reservoir pressure, production history, and engineering and abandonment practices are described in this report. The chemical and isotopic characteristics of the historic Mecca oil and natural gas are very different than those of the Clinton sandstone oil and natural gas. Gas chromatograms show that Mecca oil samples are extensively altered by biodegradation, whereas Clinton sandstone oils are not. Extensive alteration of Mecca oil is consistent with their occurrence at very shallow depths (less than 100 ft below land surface) where microbial activity can affect their composition. Also, the carbon-isotope composition of dissolved methane gas from Berea and Cussewago Sandstone water samples indicates that the gas is microbially generated, whereas the Clinton sandstone gases are thermogenically generated. Methane gas, in addition to crude oil, occurs naturally in the shallow Berea and Cussewago Sandstone aquifers in the Mosquito Creek Lake area and concentrations of dissolved methane are significant in the city of Cortland public-supply wells and in the domestic-supply wells near the southern shore of the lake. Water associated with oil and gas in the Clinton sandstone is a brine with high concentrations of chloride. Water from the Berea and Cussewago Sandstones, however, is fresh and potable. The contrasting geochemical characteristics are important for addressing water-quality issues that relate to oil and natural gas development in the Mosquito Creek area. A reexamination of the geologic framework and results of a subsurface-gas survey show that crude oil in the historic Mecca Oil Pool probably does not seep into Mosquito Creek Lake. Environmental samples show no evidence of any measurable release of oil, gas, or brine from the deeper Clinton sandstone oil and gas wells to the shallow aquifers, the lake, or lake tributaries. Brine is not associated with the hydrocarbons in the shallow Berea-Cussewago aquifer system and therefore cannot be a source of brine contamination. A mixing diagram constructed for dissolved bromide and chloride in surface water and water-supply wells shows no demonstrable mixing of these water resources with brine from the Clinton sandstone. There is some notable salinity in surface waters; however, the water is bromide poor, and a mixing diagram indicates that some local ground waters are influenced by halite solutions, presumably derived from leaching of road salt or from septic effluent.

Ohio↗
USGS2001

Natural fertility in whooping cranes and Mississippi sandhill cranes at Patuxent Wildlife Research Center

The first fertile whooping crane (Grus americana; WC) egg produced through natural breeding at Patuxent Wildlife Research Center (Patuxent) was laid in 1991. Prior to that time, all fertile whooping crane eggs were the result of artificial insemination. Since 1991, eight different whooping crane pairs at Patuxent have produced fertile eggs through natural breeding. Mean fertility averages over years for each pair range from 40% to 93%. Fertility rates for each pair also vary greatly between years, from 0% to 100% but the causes of the variance are unknown. Experiences with natural fertility in Mississippi sandhill cranes (G. canadensis pulla; MSC) have been similar. Annual natural fertility rates averaged from 21% to 89% and fertility averages for each of 7 pairs also varied greatly between years. Rearing methods have not determined success in natural breeding for either species. Both hand-reared and parent-reared pairs have been fertile. Wing condition, however, has been an important factor affecting natural fertility. Becausce artificial insemination (AI) generally results in higher fertility rates than natural breeding, Al should continue for some pairs.

Book chapter↗
USGS2011

Nature's Notebook 2010: Data & participant summary

The USA National Phenology Network (USA‐NPN) seeks to engage volunteer observers to collect phenology observations of plants and animals using consistent standards and to contribute to the USANPN National Phenology Database (NPDb). The commencement of 2010 marked the second functional year of Nature’s Notebook , the online phenology observation program developed by the National Coordinating Office (NCO) of the USA‐NPN. The addition of animal species for monitoring was a major enhancement to Nature’s Notebook in 2010. In 2010, with minimal advertising or marketing, 796 new observers registered with Nature’s Notebook and 426 observers reported phenology observations on one or more plants or animals via the online interface. Over 200,000 data records were added to the NPDb. Observations were reported on 179 species of plants and 58 species of animals. The plant species most frequently observed include red maple ( Acer rubrum ), quaking aspen ( Populus tremuloides ), American beech ( Fagus grandifolia ), northern red oak ( Quercus rubra ), and flowering dogwood ( Cornus florida ). The animal species most frequently observed were American robin ( Turdus migratorius ), black‐capped chickadee ( Poecile atricapillus ), American goldfinch ( Carduelis tristis ), bumblebee ( Bombus spp.), and white‐tailed deer ( Odocoileus virginianus ). As in 2009, participants tended to stay involved, reporting most phenophases for an average of nearly ten unique dates during the year. In addition, nearly two hundred participants who submitted observations in previous years continued to participate in 2010. This sustained participation suggests that the Nature’s Notebook interface and the status monitoring protocols inherent in Nature’s Notebook are both conducive to engaging the public and keeping them involved. Data submitted by Nature’s Notebook participants show patterns that follow latitude and elevation. Multiple years of observations now allow for year‐to‐year comparisons within and across species. As such, these data should be useful to a variety of stakeholders interested in the spatial and temporal patterns of plant and animal activity on a national scale; through time, these data should also empower scientists, resource managers, and the public in decision‐making and adapting to variable and changing climates and environments. Data submitted to Nature’s Notebook and supporting metadata are available for download at www.usanpn.org/results/data. Additionally, data visualization tools are available online at www.usanpn.org/results/visualizations.

USA-NPN Technical Series↗
USGS2013

The state of human dimensions capacity for natural resource management: needs, knowledge, and resources

The social sciences have become increasingly important in understanding natural resource management contexts and audiences, and are essential in design and delivery of effective and durable management strategies. Yet many agencies and organizations do not have the necessary resource management. We draw on the textbook definition of HD: how and why people value natural resources, what benefits people seek and derive from those resources, and how people affect and are affected by those resources and their management (Decker, Brown, and Seimer 2001). Clearly articulating how HD information can be used and integrated into natural resource management planning and decision-making is an important challenge faced by the HD field. To address this challenge, we formed a collaborative team to explore the issue of HD capacity-building for natural resource organizations and to advance the HD field. We define HD capacity as activities, efforts, and resources that enhance the ability of HD researchers and practitioners and natural managers and decision-makers to understand and address the social aspects of conservation. Specifically, we sought to examine current barriers to integration of HD into natural resource management, knowledge needed to improve HD capacity, and existing HD tools, resources, and training opportunities. We conducted a needs assessment of HD experts and practitioners, developed a framework for considering HD activities that can contribute both directly and indirectly throughout any phase of an adaptive management cycle, and held a workshop to review preliminary findings and gather additional input through breakout group discussions. This paper provides highlights from our collaborative initiative to help frame and inform future HD capacity-building efforts and natural resource organizations and also provides a list of existing human dimensions tools and resources.

The George Wright Forum↗
USGS2010

A methodology for the assessment of unconventional (continuous) resources with an application to the Greater Natural Buttes gas field, Utah

The Greater Natural Buttes tight natural gas field is an unconventional (continuous) accumulation in the Uinta Basin, Utah, that began production in the early 1950s from the Upper Cretaceous Mesaverde Group. Three years later, production was extended to the Eocene Wasatch Formation. With the exclusion of 1100 non-productive (“dry”) wells, we estimate that the final recovery from the 2500 producing wells existing in 2007 will be about 1.7 trillion standard cubic feet (TSCF) (48.2 billion cubic meters (BCM)). The use of estimated ultimate recovery (EUR) per well is common in assessments of unconventional resources, and it is one of the main sources of information to forecast undiscovered resources. Each calculated recovery value has an associated drainage area that generally varies from well to well and that can be mathematically subdivided into elemental subareas of constant size and shape called cells. Recovery per 5-acre cells at Greater Natural Buttes shows spatial correlation; hence, statistical approaches that ignore this correlation when inferring EUR values for untested cells do not take full advantage of all the information contained in the data. More critically, resulting models do not match the style of spatial EUR fluctuations observed in nature. This study takes a new approach by applying spatial statistics to model geographical variation of cell EUR taking into account spatial correlation and the influence of fractures. We applied sequential indicator simulation to model non-productive cells, while spatial mapping of cell EUR was obtained by applying sequential Gaussian simulation to provide multiple versions of reality (realizations) having equal chances of being the correct model. For each realization, summation of EUR in cells not drained by the existing wells allowed preparation of a stochastic prediction of undiscovered resources, which range between 2.6 and 3.4 TSCF (73.6 and 96.3 BCM) with a mean of 2.9 TSCF (82.1 BCM) for Greater Natural Buttes. A second approach illustrates the application of multiple-point simulation to assess a hypothetical frontier area for which there is no production information but which is regarded as being similar to Greater Natural Buttes.

Utah↗
USGS2017

Review of dynamic optimization methods in renewable natural resource management

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. Optimization methods are characterized by (1) the mathematical model used to describe a natural resource system, (2) a set of feasible strategies available to the resource manager, and (3) an objective functional by which to measure benefits and costs of strategies. A formal statement of the control problem is used to describe six approaches to optimal utilization of renewable natural resources: variational mathematics, specifically Pontryagin's Maximum Principle; dynamic programming; linear programming; nonlinear programming; simulation-optimization; and classical procedures. Solution methodologies are illustrated for each of these approaches, and examples from the ecological and natural resource literature are described for various subject matter areas. Applications are highlighted in terms of model structures, objective functionals, and system constraints. To the extent possible, optimal management patterns are characterized. Finally, the applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

Natural Resource Modeling↗
USGS2013

A natural resource condition assessment for Sequoia and Kings Canyon National Parks: Appendix 11a: giant sequoias

For natural resource managers in the southern Sierra Nevada, giant sequoia requires very little introduction. It receives great attention as an icon of western forests and as a common namesake with the areas where it occurs. While it is a single component of a very complex system, its attention in this assessment and in general is well deserved. Giant sequoia is one of the few "destination species" that attracts a wide swath of the public by nature of it simply being present. It draws people, who otherwise may not travel, to a natural environment. The result is an expansion of the public’s sense of natural resource stewardship. Because park managers could not achieve their mission without public support, this fostering role of giant sequoia is critical for park natural resources and is important for natural resources in general. Despite its social relevance and physical size, we re-emphasize here that the giant sequoia resource is a relatively small component of the ecosystems of the southern Sierra Nevada. As is the case with all of the resources assessed in the NRCA, we focus on giant sequoia with the understanding that other resources will be considered simultaneously when evaluating management decisions that impact giant sequoia. While we attempt to explicitly address the interaction of giant sequoia with other resources and stressors, we also realize that ultimately managers will integrate much more information than is presented here when making decisions that influence giant sequoia. The autecology and management issues surrounding giant sequoia have been thoroughly reviewed elsewhere (Harvey et al. 1980, Aune 1994, Stephenson 1996). Stephenson (1996), in particular, should be reviewed when considering any management decisions that potentially impact giant sequoia. For those who may not be familiar with giant sequoia ecology, a summary of basic information is provided in a table below. In some parts of this assessment, we reproduce text from Stephenson’s review because it is still relatively current for addressing some of the stressors. Numerous recent studies reported since 1996 have confirmed and expanded the understanding of giant sequoia, especially in areas related to ecophysiology and the effectiveness of restoration treatments. These recent studies are integrated into this assessment. Additionally, much unpublished work has been done that is useful for establishing baselines and evaluating trends. This work is presented in detail in order to expand upon previous work and to inform the final assessments. Instead of providing an introductory description of giant sequoia distribution and the various landowners who manage groves, we refer readers to the more recent descriptions provided by Stephenson (1996) and Willard (2000). Some of the relevant points from these descriptions with respect to giant sequoia within SEKI and Giant Sequoia National Monument (GSNM) include: - Of the native giant sequoia grove area in SEKI and GSNM approximately 38% is within SEKI and 62% is within GSNM. - 35 of the groves that make up the entire population are all or partially managed by SEKI and 33 are managed by GSNM. - As we have done above, reviewers addressing giant sequoia widely recognize its transcendence beyond an ecologically important species to one with considerable added cultural value.

California↗
USGS2008

Design of a naturalized flow regime—An example from the Lower Missouri River, USA

group of river managers, stakeholders, and scientists met during summer 2005 to design a more naturalized flow regime for the Lower Missouri River (LMOR). The objective was to comply with requirements under the U.S. Endangered Species Act to support reproduction and survival of threatened and endangered species, with emphasis on the endangered pallid sturgeon ( Scaphirhynchus albus ), while minimizing negative effects to existing social and economic benefits of prevailing river management. Specific hydrograph requirements for pallid sturgeon reproduction are unknown, hence much of the design process was based on features of the natural flow regime. Environmental flow components (EFCs) extracted from the reference natural flow regime were used to design and assess performance of alternative flow regimes. The design process incorporated a primary stage in which conceptual hydrographs were developed and assessed for their general ecological and social-economic performance. The second stage accounted for hydroclimatic variation by coding the conceptual hydrographs into reservoir release rules, adding constraints for downstream flooding and low-storage precludes, and running the rules through 100 years of hydroclimatic simulation. The output flow regimes were then evaluated for presumed ecological benefits based on how closely they resembled EFCs in the reference natural flow regime. Flow regimes also were assessed for social-economic cost indicators, including days of flooding of low-lying agricultural land, days over flood stage, and storage levels in system reservoirs. Our experience with flow-regime design on the LMOR underscored the lack of confidence the stakeholders place in the value of the natural flow regime as a measure of ecosystem benefit in the absence of fundamental scientific documentation. Stakeholders desired proof of ecological benefits commensurate with the certainty of economic losses. We also gained insight into the processes of integrating science into a collaborative management exercise. Although the 2005 collaborative effort failed to reach a consensus among stakeholders on a naturalized flow regime, the process was successful in pilot-testing a design approach; it helped focus scienctific efforts on key knowledge gaps; and it demonstrated the potential for collaborations among scientists, stakeholders, and managers in river management decision making.

Lower Missouri River↗
USGS2014

Natural flow regimes of the Ozark-Ouachita Interior Highlands region

Natural flow regimes represent the hydrologic conditions to which native aquatic organisms are best adapted. We completed a regional river classification and quantitative descriptions of each natural flow regime for the Ozark–Ouachita Interior Highlands region of Arkansas, Missouri and Oklahoma. On the basis of daily flow records from 64 reference streams, seven natural flow regimes were identified with mixture model cluster analysis: Groundwater Stable, Groundwater, Groundwater Flashy, Perennial Runoff, Runoff Flashy, Intermittent Runoff and Intermittent Flashy. Sets of flow metrics were selected that best quantified nine ecologically important components of these natural flow regimes. An uncertainty analysis was performed to avoid selecting metrics strongly affected by measurement uncertainty that can result from short periods of record. Measurement uncertainties (bias, precision and accuracy) were assessed for 170 commonly used flow metrics. The ranges of variability expected for select flow metrics under natural conditions were quantified for each flow regime to provide a reference for future assessments of hydrologic alteration. A random forest model was used to predict the natural flow regimes of all stream segments in the study area based on climate and catchment characteristics, and a map was produced. The geographic distribution of flow regimes suggested distinct ecohydrological regions that may be useful for conservation planning. This project provides a hydrologic foundation for future examination of flow–ecology relationships in the region. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Arkansas, Missouri, Oklahoma↗