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At least 55 records · Page 3Linked to original sources
USGS2012

Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop

On Thursday, May 3, 2012, a science workshop was held at the Redwood National and State Parks (RNSP) office in Arcata, California, with researchers and resource managers working in RNSP to share data and expert opinions concerning salmon populations and habitat in the Redwood Creek watershed. The focus of the workshop was to discuss how best to synthesize physical and biological data related to the freshwater and estuarine phases of salmon life cycles in order to increase the understanding of constraints on salmon populations. The workshop was hosted by the U.S. Geological Survey (USGS) Status and Trends (S&T) Program National Park Monitoring Project ( http://www.fort.usgs.gov/brdscience/ParkMonitoring.htm ), which supports USGS research on priority topics (themes) identified by the National Park Service (NPS) Inventory and Monitoring Program (I&M) and S&T. The NPS has organized more than 270 parks with significant natural resources into 32 Inventory and Monitoring (I&M) Networks ( http://science.nature.nps.gov/im/networks.cfm ) that share funding and core professional staff to monitor the status and long-term trends of selected natural resources ( http://science.nature.nps.gov/im/monitor ). All 32 networks have completed vital signs monitoring plans (available at http://science.nature.nps.gov/im/monitor/MonitoringPlans.cfm ), containing background information on the important resources of each park, conceptual models behind the selection of vital signs for monitoring the condition of natural resources, and the selection of high priority vital signs for monitoring. Vital signs are particular physical, chemical, and biological elements and processes of park ecosystems that represent the overall health or condition of the park, known or hypothesized effects of stressors, or elements that have important human values (Fancy and others, 2009). Beginning in 2009, the I&M program funded projects to analyze and synthesize the biotic and abiotic data generated by vital signs monitoring and previous in-park natural resource monitoring and inventories to provide useful information, models, and tools to park managers for addressing resource management issues. The workshop described in this report is an element of the project funded by USGS NPS-I&M program to conduct a synthesis of salmon-related datasets in the Klamath (KLMN) and San Francisco Bay Area (SFAN) networks of national parks. The synthesis focused on four park units: Redwood National Park (KLMN), Point Reyes National Seashore, Muir Woods National Monument, and Golden Gate National Recreation Area (SFAN).

California↗
USGS2015

Simulation of daily streamflow for nine river basins in eastern Iowa using the Precipitation-Runoff Modeling System

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for nine river basins in eastern Iowa that drain into the Mississippi River. The models are part of a suite of methods for estimating daily streamflow at ungaged sites. The Precipitation-Runoff Modeling System is a deterministic, distributed- parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration and validation periods used in each basin mostly were October 1, 2002, through September 30, 2012, but differed depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations. A geographic information system tool was used to delineate each basin and estimate values for model parameters based on basin physical and geographical features. A U.S. Geological Survey auto-calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The accuracy of Precipitation-Runoff Modeling System model streamflow estimates of nine river basins in eastern Iowa as compared to measured values at U.S. Geological Survey streamflow-gaging stations varied. The Precipitation-Runoff Modeling System models of nine river basins in eastern Iowa were satisfactory at estimating daily streamflow at 57 of the 79 calibration sites and 13 of the 14 validation sites based on statistical results. Unsatisfactory performance can be contributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) the availability and accuracy of meteorological input data. The Precipitation- Runoff Modeling System models of nine river basins in eastern Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

Iowa↗
USGS2017

Simulation of daily streamflow for 12 river basins in western Iowa using the Precipitation-Runoff Modeling System

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for 12 river basins in western Iowa that drain into the Missouri River. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration periods for each basin varied depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations. A geographic information system tool was used to delineate each basin and estimate initial values for model parameters based on basin physical and geographical features. A U.S. Geological Survey automatic calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values. The Precipitation-Runoff Modeling System model was calibrated at 42 sites located in the 12 river basins in western Iowa. The accuracy of the simulated daily streamflow values at the 42 calibration sites varied by river and by site. The models were satisfactory at 36 of the sites based on statistical results. Unsatisfactory performance at the six other sites can be attributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) limited availability and accuracy of meteorological input data. The Precipitation-Runoff Modeling System models of 12 river basins in western Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.

Iowa↗
USGS2021

Paths to computational fluency for natural resource educators, researchers, and managers

Natural resource management and supporting research teams need computational fluency in the data and model-rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational approaches, as well as reproducible, reusable, extensible, and transferable methods. Despite this importance, many new and current natural resource practitioners lack computational fluency and no common set of recommended resources and practices exist for learning these skills. Broadly, attaining computational fluency entails moving beyond the simple use of computers to applying sound computational principles and methods and including computational experts (such as computer scientists) on research teams. Our path for computational fluency includes using open-source tools when possible; reproducible data management, statistics, and modeling; understanding and applying the benefits of basic computer programming to carry out more complex procedures; tracking code with version control; working in controlled computer environments; and using advanced computing resources.

Natural Resource Modelling↗
USGS2024

Climate futures for lizards and snakes in western North America may result in new species management issues

We assessed changes in fundamental climate-niche space for lizard and snake species in western North America under modeled climate scenarios to inform natural resource managers of possible shifts in species distributions. We generated eight distribution models for each of 130 snake and lizard species in western North America under six time-by-climate scenarios. We combined the highest-performing models per species into a single ensemble model for each scenario. Maps were generated from the ensemble models to depict climate-niche space for each species and scenario. Patterns of species richness based on climate suitability and niche shifts were calculated from the projections at the scale of the entire study area and individual states and provinces, from Canada to Mexico. Squamate species' climate-niche space for the recent-time climate scenario and published known ranges were highly correlated ( r = 0.81). Overall, reptile climate-niche space was projected to move northward in the future. Sixty-eight percent of species were projected to expand their current climate-niche space rather than to shift, contract, or remain stable. Only 8.5% of species were projected to lose climate-niche space in the future, and these species primarily occurred in Mexico and the southwestern U.S. We found few species were projected to lose all suitable climate-niche space at the state or province level, although species were often predicted to occupy novel areas, such as at higher elevations. Most squamate species were projected to increase their climate-niche space in future climate scenarios. As climate niches move northward, species are predicted to cross administrative borders, resulting in novel conservation issues for local landowners and natural resource agencies. However, information on species dispersal abilities, landscape connectivity, biophysical tolerances, and habitat suitability is needed to contextualize predictions relative to realized future niche expansions.

Ecology and Evolution↗
USGS2016

Applying the collective impact approach to address non-native species: A case study of the Great Lakes Phragmites Collaborative

To address the invasion of non-native Phragmites in the Great Lakes, researchers at the U.S. Geological Survey—Great Lakes Science Center partnered with the Great Lakes Commission in 2012 to establish the Great Lakes Phragmites Collaborative (GLPC). The GLPC is a regional-scale partnership established to improve collaboration among stakeholders and increase the effectiveness of non-native Phragmites management and research. Rather than forming a traditional partnership with a narrowly defined goal, the GLPC follows the principles of collective impact to engage stakeholders, guide progress, and align resources to address this complex, regional challenge. In this paper, the concept and tenets of collective impact are described, the GLPC is offered as a model for other natural resource-focused collective impact efforts, and steps for establishing collaboratives are presented. Capitalizing on the interactive collective impact approach, the GLPC is moving toward a broadly accepted common agenda around which agencies and individuals will be able to better align their actions and generate measureable progress in the regional campaign to protect healthy, diverse ecosystems from damage caused by non-native Phragmites .

Biological Invasions↗
USGS2024

The 3D Elevation Program—Supporting Ohio's economy

Introduction High-quality elevation data are proving to be a resource of great economic value in dealing with many important issues in Ohio. Current and accurate high-resolution elevation data support flood risk management, water quantity and quality assessment, precision farming, conservation planning, impervious-surface modeling, forest and other natural resources management, abandoned mine and geologic hazard assessment, karst mapping, and siting of wellhead pads for horizontal drilling. These data also support coastal zone management, traffic safety and preliminary engineering site-selection studies for transportation infrastructure, solar potential and other renewable energy planning, aviation safety, and identification of features of interest or concern such as archaeological sites and orphan oil and gas wells. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features.

Ohio↗
USGS2003

Use of the Legal-Institutional Analysis Model to assess hydropower licensing negotiations

In the United States, the Federal Energy Regulatory Commission (FERC) is responsible for issuing or renewing licenses for hydropower projects owned and operated by power companies. During the licensing process, these companies are required to consult with agencies and other parties that are affected by project operating regimes. Typical participants include state and federal fish and wildlife agencies, environmental interest groups, and the FERC. One of the most difficult tasks facing participants is to reach agreement about what kinds of environmental conditions should be placed on license. Researchers at the United States Geological Survey developed a model to analyze the institutional context of natural resource disputes. The Legal-Institutional Analysis Model (LIAM) is a computerized model that allows an analyst to determine the likely behavior of each organization in a conflict. The model also analyzes the types and levels of negotiating power held by each organization. Researchers at the USGS have used the model in several cases involving hydropower license applications. To use the model, they facilitate workshops for stakeholder groups in order to develop a shared understanding of the likely obstacles and opportunities for successful resolution of the issues. This allows a systematic workshop analyses to develop strategies for successful negotiations, because they are able to better understand the negotiation problem and work more effectively with both their allies and their competitors.

Conference Paper↗
USGS2022

Engaging stakeholders to develop a decision support model of conservation risk and management capacity to prioritize investments in Bull Trout recovery

Rarely are sufficient resources available to support the full suite of management actions to promote recovery of a species across their entire distribution. Decision support models are a tool that can inform natural resource management decisions with consideration of the perspectives from a variety of stakeholders who work across large geographic and jurisdictional extents. We offer an example of a decision support model that was developed by several Federal and State natural resource agencies to rank Bull Trout Salvelinus confluentus core areas for prioritizing conservation investment within Oregon, USA. We engaged State level decision makers to identify parameters believed to be influential in determining funding allocations for Bull Trout core areas. Parameters were linked in a model framework that was further refined with input from local Bull Trout experts with knowledge specific to the various core areas. The model produces a relative priority value that is a combination of the conservation risk to the species and the management capacity to address threats. A series of sensitivity analyses suggests that Bull Trout persistence and threat score are most influential in determining the relative priority of a core area, and life-history and genetic diversity are least influential. One of the more powerful products from this work is an interactive web-based application ( https://das.ecosphere.fws.gov/public/obts/ ) that anyone can use to explore how their beliefs in parameter values will affect the relative priority of Bull Trout core areas across Oregon. Our modeling effort is an example of engaging stakeholders with different roles in species recovery and across a large geographic area to create a clearer path forward in allocating limited resources for species recovery. This approach can be employed to address a number of natural resource management situations across species and habitats.

Oregon↗
USGS2013

Use and interpretation of climate envelope models: a practical guide

This guidebook is intended to provide a practical overview of climate envelope modeling for conservation professionals and natural resource managers. The material is intended for people with little background or experience in climate envelope modeling who want to better understand and interpret models developed by others and the results generated by such models, or want to do some modeling themselves. This is not an exhaustive review of climate envelope modeling, but rather a brief introduction to some key concepts in the discipline. Readers interested in a more in-depth treatment of much of the material presented here are referred to an excellent book, Mapping Species Distributions: Spatial Inference and Prediction by Janet Franklin. Also, a recent review (Araújo & Peterson 2012) provides an excellent, though more technical, discussion of many of the issues dealt with here. Here we treat selected topics from a practical perspective, using minimal jargon to explain and illustrate some of the many issues that one has to be aware of when using climate envelope models. When we do introduce specialized terminology in the guidebook, we bold the term when it is first used; a glossary of these terms is included at the back of the guidebook.

Report↗
USGS2007

Remote sensing sensors and applications in environmental resources mapping and modeling

The history of remote sensing and development of different sensors for environmental and natural resources mapping and data acquisition is reviewed and reported. Application examples in urban studies, hydrological modeling such as land-cover and floodplain mapping, fractional vegetation cover and impervious surface area mapping, surface energy flux and micro-topography correlation studies is discussed. The review also discusses the use of remotely sensed-based rainfall and potential evapotranspiration for estimating crop water requirement satisfaction index and hence provides early warning information for growers. The review is not an exhaustive application of the remote sensing techniques rather a summary of some important applications in environmental studies and modeling.

Sensors↗
USGS2022

Analysis of per capita contributions from a spatial model provides strategies for controlling spread of invasive carp

Metapopulation models may be applied to inform natural resource management to guide actions targeted at location-specific subpopulations. Model insights frequently help to understand which subpopulations to target and highlight the importance of connections among subpopulations. For example, managers often treat aquatic invasive species populations as discrete populations due to hydrological (e.g., lakes, pools formed by dams) or jurisdictional boundaries (e.g., river segments by country or jurisdictional units such as states or provinces). However, aquatic invasive species often have high rates of dispersion and migration among heterogenous locations, which complicates traditional metapopulation models and may not conform to management boundaries. Controlling invasive species requires consideration of spatial dynamics because local management activities (e.g., harvest, movement deterrents) may have important impacts on connected subpopulations. We expand upon previous work to create a spatial linear matrix model for an aquatic invasive species, Bighead Carp, in the Illinois River, USA, to examine the per capita contributions of specific subpopulations and impacts of different management scenarios on these subpopulations. Managers currently seek to prevent Bighead Carp from invading the Great Lakes via a connection between the Illinois Waterway and Lake Michigan by allocating management actions across a series of river pools. We applied the model to highlight how spatial variation in movement rates and recruitment can affect decisions about where management activities might occur. We found that where the model suggested management actions should occur depend crucially on the specific management goal (i.e., limiting the growth rate of the metapopulation vs. limiting the growth rate of the invasion front) and the per capita recruitment rate in downstream pools. Our findings illustrate the importance of linking metapopulation dynamics to management goals for invasive species control.

Illinois↗
USGS1996

Comparison of estimated and observed stormwater runoff for fifteen watersheds in west-central Florida, using five common design techniques

Hydrologists use several traditional techniques for estimating peak discharges and runoff volumes from ungaged watersheds. However, applying these techniques to watersheds in west-central Florida requires that empirical relationships be extrapolated beyond tested ranges. As a result there is some uncertainty as to their accuracy. Sixty-six storms in 15 west-central Florida watersheds were modeled using (1) the rational method, (2) the U.S. Geological Survey regional regression equations, (3) the Natural Resources Conservation Service (formerly the Soil Conservation Service) TR-20 model, (4) the Army Corps of Engineers HEC-1 model, and (5) the Environmental Protection Agency SWMM model. The watersheds ranged between fully developed urban and undeveloped natural watersheds. Peak discharges and runoff volumes were estimated using standard or recommended methods for determining input parameters. All model runs were uncalibrated and the selection of input parameters was not influenced by observed data. The rational method, only used to calculate peak discharges, overestimated 45 storms, underestimated 20 storms and estimated the same discharge for 1 storm. The mean estimation error for all storms indicates the method overestimates the peak discharges. Estimation errors were generally smaller in the urban watersheds and larger in the natural watersheds. The U.S. Geological Survey regression equations provide peak discharges for storms of specific recurrence intervals. Therefore, direct comparison with observed data was limited to sixteen observed storms that had precipitation equivalent to specific recurrence intervals. The mean estimation error for all storms indicates the method over estimates both peak discharges and runoff volumes. Estimation errors were smallest for the larger natural watersheds in Sarasota County, and largest for the small watersheds located in the eastern part of the study area. The Natural Resources Conservation Service TR-20 model, overestimated peak discharges for 45 storms and underestimated 21 storms, and overestimated runoff volumes for 44 storms and underestimated 22 storms. The mean estimation error for all storms modeled indicates that the model overestimates peak discharges and runoff volumes. The smaller estimation errors in both peak discharges and runoff volumes were for storms occurring in the urban watersheds, and the larger errors were for storms occurring in the natural watersheds. The HEC-1 model overestimated peak discharge rates for 55 storms and underestimated 11 storms. Runoff volumes were overestimated for 44 storms and underestimated for 22 storms using the Army Corps of Engineers HEC-1 model. The mean estimation error for all the storms modeled indicates that the model overestimates peak discharge rates and runoff volumes. Generally, the smaller estimation errors in peak discharges were for storms occurring in the urban watersheds, and the larger errors were for storms occurring in the natural watersheds. Estimation errors in runoff volumes; however, were smallest for the 3 natural watersheds located in the southernmost part of Sarasota County. The Environmental Protection Agency Storm Water Management model produced similar peak discharges and runoff volumes when using both the Green-Ampt and Horton infiltration methods. Estimated peak discharge and runoff volume data calculated with the Horton method was only slightly higher than those calculated with the Green-Ampt method. The mean estimation error for all the storms modeled indicates the model using the Green-Ampt infiltration method overestimates peak discharges and slightly underestimates runoff volumes. Using the Horton infiltration method, the model overestimates both peak discharges and runoff volumes. The smaller estimation errors in both peak discharges and runoff volumes were for storms occurring in the five natural watersheds in Sarasota County with the least amount of impervious cover and the lowest slopes. The largest errors were for storms occurring in the three small natural watersheds in the eastern part of the study area. The mean estimation errors for peak discharge ranged from an underestimation of 63 percent to an overestimation of 224 percent. For runoff volume, the mean estimation errors range from an underestimation of 63.3 percent to an overestimation of 267 percent.

Florida↗
USGS2019

Successful molecular detection studies require clear communication among diverse research partners

Molecular detection techniques are powerful tools used in ecological applications ranging from diet analyses to pathogen surveillance. Research partnerships that use these tools often involve collaboration among professionals with expertise in field biology, laboratory techniques, quantitative modeling, wildlife disease, and natural resource management. However, in many cases, each of these collaborators lacks specific knowledge about the approaches, decisions, methods, and terminology used by their research partners, which can impede effective communication and act as a barrier to the efficient use of molecular data for ecological inferences and subsequent conservation decision making. We outline a collaborative framework to assist colleagues with diverse types of expertise to effectively translate their scientific and management needs to research partners from other specialties. The molecular techniques used to detect organisms will continue to advance both in sophistication and in the breadth of ecological applications. Our objective is to enable ecologists to harness the full utility of these methods by developing effective collaborative partnerships.

Frontiers in Ecology and the Environment↗
USGS2020

InFish: A professional network to promote global conservation and responsible use of inland fish

Inland fishes and fisheries make substantial contributions to individuals, society, and the environment in a changing global landscape that includes climate, water allocations, and societal changes. However, current limitations to valuing the services provided by inland fish and their fisheries often leaves them out of key decision‐making discussions. InFish is a voluntary professional network with over 120 members from over 50 organizations in over 20 countries that seeks to address challenges facing inland fish through novel approaches and international collaborations. InFish fosters opportunities to share knowledge, pursue proposals, publications, and conference‐related events focused on inland fisheries. InFish has become a source of inland fisheries expertise, working collectively towards global conservation and sustainable use of inland fish through informing scientifically sound management practices. As such, InFish may serve as a model network for other natural resource challenges now and into the future.

Fisheries Magazine↗
USGS2011

Hydrostratigraphic interpretation of test-hole and geophysical data, Upper Loup River Basin, Nebraska, 2008-10

Nebraska's Upper Loup Natural Resources District is currently (2011) participating in the Elkhorn-Loup Model to understand the effect of various groundwater-management scenarios on surface-water resources. During Phase 1 of the Elkhorn-Loup Model, a lack of subsurface geological information in the Upper Loup Natural Resources District, hereafter referred to as the upper Loup study area, was identified as a gap in current knowledge that needed to be addressed. To improve the understanding of the hydrogeology of the upper Loup study area, the U.S. Geological Survey, in cooperation with the Upper Loup Natural Resources District and the University of Nebraska Conservation and Survey Division, collected and described the lithology of drill cuttings from nine test holes, and concurrently collected borehole geophysical data to identify the base of the High Plains aquifer. Surface geophysical data also were collected using time-domain electromagnetic (TDEM) and audio-magnetotelluric (AMT) methods at test-hole locations and between test holes, as a quick, non-invasive means of identifying the base of the High Plains aquifer. Test-hole drilling has indicated greater variation in the base-of-aquifer elevation in the western part of the upper Loup study area than in the eastern part reflecting a number of deep paleovalleys incised into the Brule Formation of the White River Group. TDEM measurements within the upper Loup study area were shown to be effective as virtual boreholes in mapping out the base of the aquifer. TDEM estimates of the base of aquifer were in good accordance with existing test-hole data and were able to improve the interpreted elevation and topology of the base of the aquifer. In 2010, AMT data were collected along a profile, approximately 12 miles (19 kilometers) in length, along Whitman Road, in Grant and Cherry Counties. The AMT results along Whitman Road indicated substantial variability in the elevation of the base of the High Plains aquifer and in the distribution of highly permeable zones within the aquifer.

Open-File Report↗
USGS2020

Water balance as an indicator of natural resource condition: Case studies from Great Sand Dunes National Park and Preserve

Managing climate impacts to natural resources in protected areas can be hampered by lack of monitoring data, poor understanding of natural resource responses to climate, or lack of timely condition assessments that can inform management actions. Here we demonstrate the utility of water balance as a tool for understanding natural resource responses to climate by developing case studies focused on stream flow, vegetation production, and wildfire ignition at Great Sand Dunes National Park and Preserve (GSDNP), U.S.A. The efficacy of water balance to predict these responses stems from the explicit integration of climate with site conditions that modify the effects of climate. This in turn results in estimates of water availability, water use, and water need that are proximal drivers of aquatic and terrestrial natural resource conditions. The water balance model successfully forecasted stream flow (r 2 = 0.69, P < 0.001); determined the critical water needs for maintaining annual vegetation production in different vegetation types spanning a large environmental gradient (r 2 = 0.18–0.71); and predicted proportion of historic wildfire ignitions in forest (r 2 = 0.96–0.99) and non-forest (r 2 = 0.96–0.97) vegetation types. Collectively, these case studies demonstrate practical approaches to translate climate data into assessments of natural resource condition that inform long-term planning and near-term strategic actions needed for conservation of protected areas.

Great Sand Dunes National Park and Preserve↗