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USGS2011

Range-wide assessment of livestock grazing across the sagebrush biome

Domestic livestock grazing occurs in virtually all sagebrush habitats and is a prominent disturbance factor. By affecting habitat condition and trend, grazing influences the resources required by, and thus, the distribution and abundance of sagebrush-obligate wildlife species (for example, sage-grouse Centrocercus spp.). Yet, the risks that livestock grazing may pose to these species and their habitats are not always clear. Although livestock grazing intensity and associated habitat condition may be known in many places at the local level, we have not yet been able to answer questions about use, condition, and trend at the landscape scale or at the range-wide scale for wildlife species. A great deal of information about grazing use, management regimes, and ecological condition exists at the local level (for individual livestock management units) under the oversight of organizations such as the Bureau of Land Management (BLM). However, the extent, quality, and types of existing data are unknown, which hinders the compilation, mapping, or analysis of these data. Once compiled, these data may be helpful for drawing conclusions about rangeland status, and we may be able to identify relationships between those data and wildlife habitat at the landscape scale. The overall objective of our study was to perform a range-wide assessment of livestock grazing effects (and the relevant supporting data) in sagebrush ecosystems managed by the BLM. Our assessments and analyses focused primarily on local-level management and data collected at the scale of BLM grazing allotments (that is, individual livestock management units). Specific objectives included the following: 1. Identify and refine existing range-wide datasets to be used for analyses of livestock grazing effects on sagebrush ecosystems. 2. Assess the extent, quality, and types of livestock grazing-related natural resource data collected by BLM range-wide (i.e., across allotments, districts and regions). 3. Compile and synthesize recommendations from federal and university rangeland science experts about how BLM might prioritize collection of different types of livestock grazing-related natural resource data. 4. Investigate whether range-wide datasets (Objective 1) could be used in conjunction with remotely sensed imagery to identify across broad scales (a) allotments potentially not meeting BLM Land Health Standards (LHS) and (b) allotments in which unmet standards might be attributable to livestock grazing. Objective 1: We identified four datasets that potentially could be used for analyses of livestock grazing effects on sagebrush ecosystems. First, we obtained the most current spatial data (typically up to 2007, 2008, or 2009) for all BLM allotments and compiled data into a coarse, topologically enforced dataset that delineated grazing allotment boundaries. Second, we obtained LHS evaluation data (as of 2007) for all allotments across all districts and regions; these data included date of most recent evaluation, BLM determinations of whether region-specific standards were met, and whether BLM deemed livestock to have contributed to any unmet standards. Third, we examined grazing records of three types: Actual Use (permittee-reported), Billed Use (BLM-reported), and Permitted Use (legally authorized). Finally, we explored the possibility of using existing Natural Resources Conservation Service (NRCS) Ecological Site Description (ESD) data to make up-to-date estimates of production and forage availability on BLM allotments. Objective 2: We investigated the availability of BLM livestock grazing-related monitoring data and the status of LHS across 310 randomly selected allotments in 13 BLM field offices. We found that, relative to other data types, the most commonly available monitoring data were Actual Use numbers (permittee-reported livestock numbers and season-of-use), followed by Photo Point, forage Utilization, and finally, Vegetation Trend measurement data. Data availability and frequency of data collection varied across allotments and field offices. Analysis of the BLM's LHS data indicated 67 percent of allotments analyzed were meeting standards. For those not meeting standards, livestock were considered the causal factor in 45 percent of cases (about 15 percent of all allotments). Objective 3: We sought input from 42 university and federal rangeland science experts about how best to prioritize rangeland monitoring activities associated with ascertaining livestock impacts on vegetation resources. When we presented a hypothetical scenario to these scientists and asked them to prioritize monitoring activities, the most common response was to measure ground and vegetation cover, a variable that in many cases (10 of 13 field offices sampled) BLM had already identified as a monitoring priority. Experts identified several other traditional (for example, photo points) and emerging approaches (for example, high-resolution aerial photography) to monitoring. Objective 4: We used spatial allotment data (described in Objective 1) and remotely sensed vegetation data (sagebrush cover, herbaceous vegetation cover, litter and bare soil) to assess differences in allotment LHS status ("Not met" vs. "Met"; if "Not met" - livestock-caused vs. not). We then developed logistic regression models, using vegetation variables to predict LHS status of BLM allotments in sagebrush steppe habitats in Wyoming and portions of Montana and Colorado. In general, we found that more consistent data collection at the local level might improve suitability of data for broad-scale analyses of livestock impacts. As is, data collection methodologies varied across field offices and States, and we did not find any local-level monitoring data (Actual Use, Utilization, Vegetation Trend) that had been collected consistently enough over time or space for range-wide analyses. Moreover, continued and improved emphasis on monitoring also may aid local management decisions, particularly with respect to effects of livestock grazing. Rangeland science experts identified ground cover as a high monitoring priority for assessing range condition and emphasized the importance of tracking livestock numbers and grazing dates. Ultimately, the most effective monitoring program may entail both increased data collection effort and the integration of alternative monitoring approaches (for example, remote sensing or monitoring teams). In the course of our study, we identified three additional datasets that could potentially be used for range-wide analyses: spatial allotment boundary data for all BLM allotments range-wide, LHS evaluations of BLM allotments, and livestock use data (livestock numbers and grazing dates). It may be possible to use these spatial datasets to help prioritize monitoring activities over the extensive land areas managed by BLM. We present an example of how we used spatial allotment boundary data and LHS data to test whether remotely sensed vegetation characteristics could be used to predict which allotments met or did not meet LHS. This approach may be further improved by the results of current efforts by BLM to test whether more intensive (higher resolution) LHS assessments more accurately describe land health status. Standardized data collection in more ecologically meaningful land units may improve our ability to use local-level data for broad-scale analyses.

Open-File Report↗

USGS2000

Reserve growth effects on estimates of oil and natural gas resources

Many scientists think that the supply of economically recoverable oil and natural gas is geologically limited. However, as recently as early 1999, we experienced a glut of oil on the world market and the lowest inflation-adjusted price of gasoline in history. What is going on? While we cannot provide a comprehensive answer to that question here, we can describe one process that significantly affects the domestic oil and gas industry, a process that also will affect the global industry at some point—reserve growth (also known as field growth).

Fact Sheet↗

USGS2006

Simulation of nutrient and sediment concentrations and loads in the Delaware inland bays watershed: Extension of the hydrologic and water-quality model to ungaged segments

Rapid population increases, agriculture, and industrial practices have been identified as important sources of excessive nutrients and sediments in the Delaware Inland Bays watershed. The amount and effect of excessive nutrients and sediments in the Inland Bays watershed have been well documented by the Delaware Geological Survey, the Delaware Department of Natural Resources and Environmental Control, the U.S. Environmental Protection Agency’s National Estuary Program, the Delaware Center for Inland Bays, the University of Delaware, and other agencies. This documentation and data previously were used to develop a hydrologic and water-quality model of the Delaware Inland Bays watershed to simulate nutrients and sediment concentrations and loads, and to calibrate the model by comparing concentrations and streamflow data at six stations in the watershed over a limited period of time (October 1998 through April 2000). Although the model predictions of nutrient and sediment concentrations for the calibrated segments were fairly accurate, the predictions for the 28 ungaged segments located near tidal areas, where stream data were not available, were above the range of values measured in the area. The cooperative study established in 2000 by the Delaware Department of Natural Resources and Environmental Control, the Delaware Geological Survey, and the U.S. Geological Survey was extended to evaluate the model predictions in ungaged segments and to ensure that the model, developed as a planning and management tool, could accurately predict nutrient and sediment concentrations within the measured range of values in the area. The evaluation of the predictions was limited to the period of calibration (1999) of the 2003 model. To develop estimates on ungaged watersheds, parameter values from calibrated segments are transferred to the ungaged segments; however, accurate predictions are unlikely where parameter transference is subject to error. The unexpected nutrient and sediment concentrations simulated with the 2003 model were likely the result of inappropriate criteria for the transference of parameter values. From a model-simulation perspective, it is a common practice to transfer parameter values based on the similarity of soils or the similarity of land-use proportions between segments. For the Inland Bays model, the similarity of soils between segments was used as the basis to transfer parameter values. An alternative approach, which is documented in this report, is based on the similarity of the spatial distribution of the land use between segments and the similarity of land-use proportions, as these can be important factors for the transference of parameter values in lumped models. Previous work determined that the difference in the variation of runoff due to various spatial distributions of land use within a watershed can cause substantialloss of accuracy in the model predictions. The incorporation of the spatial distribution of land use to transfer parameter values from calibrated to uncalibrated segments provided more consistent and rational predictions of flow, especially during the summer, and consequently, predictions of lower nutrient concentrations during the same period. For the segments where the similarity of spatial distribution of land use was not clearly established with a calibrated segment, the similarity of the location of the most impervious areas was also used as a criterion for the transference of parameter values. The model predictions from the 28 ungaged segments were verified through comparison with measured in-stream concentrations from local and nearby streams provided by the Delaware Department of Natural Resources and Environmental Control. Model results indicated that the predicted edge-of-stream total suspended solids loads in the Inland Bays watershed were low in comparison to loads reported for the Eastern Shore of Maryland from the Chesapeake Bay watershed model. The flatness of the terrain and the low annual surface runoff are important factors in determining the amount of detached sediment from the land that is delivered to streams. The highest predicted total suspended solids loads were found in the southern part of the watershed, where the values are associated with high total streamflow and a high surface-runoff component, and related to soil and aquifer permeability and land use. Nutrient loads from model segments in the southern part of the Inland Bays watershed were also higher than those measured in the northern part of the basin, due to relatively high runoff and the substantial amount of available organic fertilizer (animal waste) that results in over-application of organic fertilizer to crops. Time series of simulated hourly concentrations indicated a seasonal pattern in the simulated base flow for total nitrogen, with the lowest values occurring during the summer and the highest values during the winter months. Total phosphorus and total-suspended-solids concentrations were less seasonal and were more storm-dependent; in general, base-flow concentrations of total phosphorus and total suspended solids were low. During storm events, the total nitrogen concentrations tended to be diluted and total phosphorus concentrations tended to rise sharply. Nitrogen was transported mainly in the aqueous phase and largely through ground water, whereas phosphorus was strongly associated with sediment, which washes off during rainfall events.

Delaware↗

USGS2013

Priority data on marine and estuarine resources within northeastern National Parks: Inventory and acquisition needs

The purpose of this project was to guide development of a strategy for the inventory and mapping of submerged natural resources associated within 10 coastal parks of the National Park Service (NPS) Northeast Region (NER; see Table 1). Priority data needs were identified by the NER Ocean Stewardship Task Force. The majority of the NER priority data needs involve the biotic, chemical, and geological characterization of the seabed. Taken collectively, this demands a consistent and unified approach to habitat classification. The Coastal and Marine Ecological Classification Standard (CMECS) is endorsed by the Federal Geographic Data Committee (FGDC-STD-018) for classifying ecological units in coastal and marine environments, and is recommended as a framework for acquiring and organizing NER data. We prepared an inventory of existing data on priority marine and estuarine natural resources within the ten NER coastal parks. This report describes the data and information sources relevant to each park and identifies gaps in available data. Overwhelmingly and uniformly across all parks, the most pressing needs are consistent, high-resolution bathymetry and seafloor characterization data. Approaches for acquiring these data using an integrated, multi-resolution sampling framework are recommended.

Natural Resource Report↗

USGS2013

Challenge theme 5: Current and future needs of energy and mineral resources in the Borderlands and the effects of their development: Chapter 7 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science

Exploration and extraction activities related to energy and mineral resources in the Borderlands—such as coal-fired power plants, offshore drilling, and mining—can create issues that have potentially major economic and environmental implications. Resource assessments and development projects, environmental studies, and other related evaluations help to understand some of these issues, such as power plant emissions and the erosion/denudation of abandoned mine lands. Information from predictive modeling, monitoring, and environmental assessments are necessary to understand the full effects of energy and mineral exploration, development, and utilization. The exploitation of these resources can negatively affect human health and the environment, its natural resources, and its ecological services (air, water, soil, recreation, wildlife, etc.). This chapter describes the major energy and mineral issues of the Borderlands and how geologic frameworks, integrated interdisciplinary (geobiologic) investigations, and other related studies can address the anticipated increases in demands on natural resources in the region.

United States-Mexico Borderlands↗

USGS1999

Assessment of landslide hazards in Kaluanui and Maakua gulches, Oahu, Hawaii, following the 9 May 1999 Sacred Falls landslide

One of the injured hikers later died of injuries received in the landslide. Governor Ben Cayetano of Hawaii ordered that the park be closed due to concern about continuing landslide hazard near the falls. Subsequently, Bill Meyer, District Chief for the U.S. Geological Survey (USGS) Water Resources Division in Honolulu contacted Tim Johns, Chair of the Board of Land and Natural Resources of the Hawaii Department of Land and Natural Resources (DLNR) and offered assistance in assessing slope stability in the park. Mr. Johns accepted the offer, and two landslide specialists from the USGS Geologic Hazards Team in Golden Colorado were sent to the site. On Friday, 14 May 1999, we visited the Sacred Falls landslide site with Glenn Bauer, Ed Sakoda, and Gary Moniz of DLNR. The ground investigation involved inspecting the impact area, estimating the volume of the deposit, and gathering data to help reconstruct the event. On Monday, 17 May 1999, we conducted an aerial reconnaissance of Kaluanui Gulch (Sacred Falls State Park) and Maakua Gulch in a commercial helicopter provided by DLNR. We inspected the source and path of movement of the Sacred Falls landslide of 9 May and reconnoitered the full length of both valleys to get an overview of ongoing landslide hazards there. This report gives our observations and conclusions about the Sacred Falls landslide, broadly assesses the ongoing hazard in the Kaluanui and Maakua Gulches, and suggests methods for more detailed assessment of landslide hazards here and along other trails in state parks on Oahu. Observations and conclusions in this report are based on a very brief investigation and thus are preliminary in nature.

Hawaii↗

USGS2001

Geologic studies of deep natural gas resources

In 1995, the USGS estimated a mean resource of 114 trillion cubic feet of undiscovered technically recoverable natural gas in plays deeper than 15,000 feet/4,572 meters in onshore regions of the United States. This volume summarizes major conclusions of ongoing work. Chapters A and B address the areal extent of drilling and distribution of deep basins in the U.S. Chapter C summarizes distribution of deep sedimentary basins and potential for deep gas in the former Soviet Union. Chapters D and E are geochemical papers addressing source-rock issues and deep gas generation. Chapter F develops a probabilistic method for subdividing gas resources into depth slices, and chapter G analyzes the relative uncertainty of estimates of deep gas in plays in the Gulf Coast Region. Chapter H evaluates the mechanism of hydrogenation of deep, high-rank spent kerogen by water, with subsequent generation of methane-rich HC gas.

Data Series↗

USGS2024

Restoration monitoring metric framework: Integrating innovative remote-sensing technologies: Comparisons between field and remotely sensed vegetation surveys of restored forested and grassland sites in Ohio

Restoration monitoring is generally perceived as costly and time-consuming, yet the concept of universal restoration monitoring metrics is trending for evaluation of restoration performance across spatial scales, project boundaries, and jurisdictions. Natural Resource Damage Assessment and Restoration (NRDAR) practitioners seek to restore natural resources injured by oil spills or hazardous substance releases into the environment. Therefore, a multiagency team [US Army Engineer Research and Development Center (ERDC), US Department of the Interior (DOI), and US Department of Energy (DOE)] developed and field-tested a multitiered monitoring framework, illustrating a range of field and remote-sensing techniques and methodologies. The restoration monitoring framework and field demonstration offer a unique methodology to acquire and evaluate simultaneously collected, multiscale/multiplatform data. The result of this research provides new insights to (1) assist planning, implementing, and monitoring restoration progress and effectiveness; and (2) apply common monitoring methods, endpoints, and metrics to other types of ecosystem restoration initiatives. Although the aim was to inform monitoring and management of areas that had been injured, these methods could also be used to inform restoration monitoring practices in a broader context, benefiting environmental stewardship missions of all project partners.

Final Technical Report↗

USGS2006

The Environmental Monitoring and Assessment Program (EMAP)-West: Summary of activities and accomplishments in South Dakota, 2000-2004

The Environmental Monitoring and Assessment Program (EMAP)-West was initiated in South Dakota in 2000 by the U.S. Environmental Protection Agency (USEPA). The two primary objectives of the surface waters component of EMAP-West were to (1) develop the monitoring tools (biological indicators, stream survey design, estimates of reference condition) necessary to produce unbiased estimates of the ecological condition of surface waters across a large geographic area of the West; and (2) demonstrate the effectiveness of those tools in a large-scale assessment. Although not specifically defined as an objective, data collected during EMAP-West also will help to establish a baseline for comparisons with data obtained from future monitoring efforts and could document changing biological conditions resulting from changing land-use or land-management practices associated with regulatory or restorative efforts. EMAP-West is a partnership between USEPA, States, Tribes, and other interested parties in USEPA Regions 8, 9, and 10. In South Dakota, the principle EMAP-West cooperators include the USEPA, South Dakota Department of Game, Fish and Parks (GF&P), and the U.S. Geological Survey (USGS). Other agencies such as the Natural Resource Conservation Service, the South Dakota Department of Environment and Natural Resources (SDDENR), State Conservation Districts, and various Tribal departments also have provided valuable expertise and assistance. This fact sheet summarizes the activities and accomplishments associated with EMAP-West in South Dakota during 2000–2004. Efforts were focused on perennial streams that usually can be waded. Large rivers also were assessed during EMAP-West under the auspices of USEPA using boats and similar techniques, but are not included in the activities discussed here. Data-collection activities for wadeable streams were conducted under the auspices of USEPA in South Dakota during 2000 and by the USGS during 2001–2004. A more detailed description of EMAP-West activities and assessments in South Dakota is available in Heakin and others ( in press ).

South Dakota↗

USGS2010

Great Basin Integrated Landscape Monitoring Pilot Summary Report

The Great Basin Integrated Landscape Monitoring Pilot project (GBILM) was one of four regional pilots to implement the U.S. Geological Survey (USGS) Science Thrust on Integrated Landscape Monitoring (ILM) whose goal was to observe, understand, and predict landscape change and its implications on natural resources at multiple spatial and temporal scales and address priority natural resource management and policy issues. The Great Basin is undergoing rapid environmental change stemming from interactions among global climate trends, increasing human populations, expanding and accelerating land and water uses, invasive species, and altered fire regimes. GBLIM tested concepts and developed tools to store and analyze monitoring data, understand change at multiple scales, and forecast landscape change. The GBILM endeavored to develop and test a landscape-level monitoring approach in the Great Basin that integrates USGS disciplines, addresses priority management questions, catalogs and uses existing monitoring data, evaluates change at multiple scales, and contributes to development of regional monitoring strategies. GBILM functioned as an integrative team from 2005 to 2010, producing more than 35 science and data management products that addressed pressing ecosystem drivers and resource management agency needs in the region. This report summarizes the approaches and methods of this interdisciplinary effort, identifies and describes the products generated, and provides lessons learned during the project.

Open-File Report↗

USGS2020

Introduction to resource allocation

With ongoing habitat loss and degradation, ever-increasing threats to biodiversity, and limited funding for conservation and management, nearly every natural resource manager routinely faces difficult resource allocation problems. Funding and capacity for natural resource management rarely meet the need, and informed resource allocations are increasingly important. These decision problems include not only habitat and species management but also a wide variety of administrative decisions. Ranking projects or plans by benefit-cost ratio is an intuitive, heuristic approach to resource allocation but may be inefficient. We present a general resource allocation framework in which these decision problems can be stated mathematically, making it relatively easy to find solutions using mathematical programming such as linear programming. amenable to Linear programming and other constrained optimization routines, which can be implemented in common software applications and used with a wide variety of decision problems, including project prioritization and portfolio decisions. Constrained optimization has advantages over intuitive benefit-cost ratios and can accommodate single and multiple objective problems. We also introduce the three case studies in this section illustrating a variety of resource allocation problems: the first case study shows how to select cost-effective management actions for discrete management units such as wetlands or grassland patches; the second, how to use a patch dynamics model to allocation allocate resources for a reserve network that protects habitat for multiple species of conservation concern; and the third, how to use stochastic simulation to determine allocation of resources in space and time for invasive species management.

Book chapter↗

USGS2009

Capacitively Coupled Resistivity Survey of Selected Irrigation Canals Within the North Platte River Valley, Western Nebraska and Eastern Wyoming, 2004 and 2007-2009

Due to water resources of portions of the North Platte River basin being designated as over-appropriated by the State of Nebraska Department of Natural Resources (DNR), the North Platte Natural Resources District (NPNRD), in cooperation with the DNR, is developing an Integrated Management Plan (IMP) for groundwater and surface water in the NPNRD. As part of the IMP, a three-dimensional numerical finite difference groundwater-flow model is being developed to evaluate the effectiveness of using leakage of water from selected irrigation canal systems to manage groundwater recharge. To determine the relative leakage potential of the upper 8 m of the selected irrigation canals within the North Platte River valley in western Nebraska and eastern Wyoming, the U.S. Geological Survey performed a land-based capacitively coupled (CC) resistivity survey along nearly 630 km of 13 canals and 2 laterals in 2004 and from 2007 to 2009. These 13 canals were selected from the 27 irrigation canals in the North Platte valley due to their location, size, irrigated area, and relation to the active North Platte valley flood plain and related paleochannels and terrace deposits where most of the saturated thickness in the alluvium exists. The resistivity data were then compared to continuous cores at 62 test holes down to a maximum depth of 8 m. Borehole electrical conductivity (EC) measurements at 36 of those test holes were done to correlate resistivity values with grain sizes in order to determine potential vertical leakage along the canals as recharge to the underlying alluvial aquifer. The data acquired in 2004, as well as the 25 test hole cores from 2004, are presented elsewhere. These data were reprocessed using the same updated processing and inversion algorithms used on the 2007 through 2009 datasets, providing a consistent and complete dataset for all collection periods. Thirty-seven test hole cores and borehole electrical conductivity measurements were acquired based on the 2008 data. This report presents comparisons between the CC resistivity data and results from the 37 test holes and includes all binned and inverted CC resistivity datasets from all four years as well as the EC log data for the 37 test holes acquired in 2008 and 2009. The information gained from these data can help State and local water managers and scientists better understand the characteristics of the shallow subsurface underlying the irrigation canals so that the water resources can be managed more effectively.

Scientific Investigations Report↗

USGS2017

National Park Service Vegetation Mapping Inventory Program: Appalachian National Scenic Trail vegetation mapping project

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program classifies, describes, and maps existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Northeast Temperate Network, and NPS Appalachian National Scenic Trail (APPA) have completed vegetation classification and mapping of APPA for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of APPA and to determine how best to map the vegetation types by using aerial imagery. Analyses of data from 1,618 vegetation plots were used to describe USNVC associations of APPA. Data from 289 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Data from 269 validation sites were collected to assess vegetation mapping prior to submitting the vegetation map for accuracy assessment (AA). Data from 3,265 AA sites were collected, of which 3,204 were used to test accuracy of the vegetation map layer. The collective of these datasets affirmed 280 USNVC associations for the APPA vegetation mapping project. To map the vegetation and land cover of APPA, 169 map classes were developed. The 169 map classes consist of 150 that represent natural (including ruderal) vegetation types in the USNVC, 11 that represent cultural (agricultural and developed) vegetation types in the USNVC, 5 that represent natural landscapes with catastrophic disturbance or some other modification to natural vegetation preventing accurate classification in the USNVC, and 3 that represent nonvegetated water (non-USNVC). Features were interpreted from viewing 4-band digital aerial imagery using digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). (Digital aerial imagery was collected each fall during 2009–11 to capture leaf-phenology change of hardwood trees across the latitudinal range of APPA.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in GIS. Polygon units were mapped to either a 0.5-hectare (ha) or 0.25-ha minimum mapping unit, depending on vegetation type or scenario; however, polygon units were mapped to 0.1 ha for alpine vegetation. A geodatabase containing various feature-class layers and tables provide locations and support data to USNVC vegetation types (vegetation map layer), vegetation plots, verification sites, validation sites, AA sites, project boundary extent and zones, and aerial image centers and flight lines. The feature-class layer and related tables of the vegetation map layer provide 30,395 polygons of detailed attribute data covering 110,919.7 ha, with an average polygon size of 3.6 ha; the vegetation map coincides closely with the administrative boundary for APPA. Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 28,242 polygons (92.9% of polygons) and cover 106,413.0 ha (95.9%) of the map extent for APPA. The map layer indicates APPA to be 92.4% forest and woodland (102,480.8 ha), 1.7% shrubland (1866.3 ha), and 1.8% herbaceous cover (2,065.9 ha). Map classes representing park-special vegetation (undefined in the USNVC) apply to 58 polygons (0.2% of polygons) and cover 404.3 ha (0.4%) of the map extent. Map classes representing USNVC cultural types apply to 1,777 polygons (5.8% of polygons) and cover 2,516.3 ha (2.3%) of the map extent. Map classes representing nonvegetated water (non-USNVC) apply to 332 polygons (1.1% of polygons) and cover 1,586.2 ha (1.4%) of the map extent.

Appalachian National Scenic Trail↗

USGS2016

National Park Service Vegetation Mapping Inventory Program: Natchez Trace Parkway vegetation mapping project report

The National Park Service (NPS) Vegetation Mapping Inventory (VMI) Program is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&M) Program. The NPS VMI Program is managed by the NPS I&M Division and provides baseline vegetation information to the NPS Natural Resource I&M Program. The U.S. Geological Survey Upper Midwest Environmental Sciences Center, NatureServe, NPS Gulf Coast Network, and NPS Natchez Trace Parkway (NATR; also referred to as Parkway) have completed vegetation classification and mapping of NATR for the NPS VMI Program. Mappers, ecologists, and botanists collaborated to affirm vegetation types within the U.S. National Vegetation Classification (USNVC) of NATR and to determine how best to map them by using aerial imagery. Analyses of data from 589 vegetation plots had been used to describe an initial 99 USNVC associations in the Parkway; this classification work was completed prior to beginning this NATR vegetation mapping project. Data were collected during this project from another eight quick plots to support new vegetation types not previously identified at the Parkway. Data from 120 verification sites were collected to test the field key to vegetation associations and the application of vegetation associations to a sample set of map polygons. Furthermore, data from 900 accuracy assessment (AA) sites were collected (of which 894 were used to test accuracy of the vegetation map layer). The collective of all these datasets resulted in affirming 122 USNVC associations at NATR. To map the vegetation and open water of NATR, 63 map classes were developed. including the following: 54 map classes represent natural (including ruderal) vegetation types in the USNVC, 5 map classes represent cultural (agricultural and developed) vegetation types in the USNVC, 3 map classes represent nonvegetation open-water bodies (non-USNVC), and 1 map class represents landscapes that had received tornado damage a few months prior to the time of aerial imagery collection. Features were interpreted from viewing 4-band digital aerial imagery by means of digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems. (The aerial imagery was collected during mid-October 2011 for the northern reach of the Parkway and mid-November 2011 for the southern reach of the Parkway to capture peak leaf-phenology of trees.) The interpreted data were digitally and spatially referenced, thus making the spatial-database layers usable in geographic information systems. Polygon units were mapped to either a 0.5 hectare (ha) or 0.25 ha minimum mapping unit, depending on vegetation type or scenario. A geodatabase containing various feature-class layers and tables present the locations of USNVC vegetation types (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial image centers. The feature-class layer and related tables for the vegetation map provide 13,529 polygons of detailed attribute data covering 21,655.5 ha, with an average polygon size of 1.6 ha; the vegetation map coincides closely with the administrative boundary for NATR. Summary reports generated from the vegetation map layer of the map classes representing USNVC natural (including ruderal) vegetation types apply to 12,648 polygons (93.5% of polygons) and cover 18,542.7 ha (85.6%) of the map extent for NATR. The map layer indicates the Parkway to be 70.5% forest and woodland (15,258.7 ha), 0.3% shrubland (63.0 ha), and 14.9% herbaceous cover (3,221.0 ha). Map classes representing USNVC cultural types apply to 678 polygons (5.0% of polygons) and cover 2,413.9 ha (11.1%) of the map extent.

Natural Resource Report↗

USGS2010

Quantifying canal leakage rates using a mass-balance approach and heat-based hydraulic conductivity estimates in selected irrigation canals, western Nebraska, 2007 through 2009

The water supply in areas of the North Platte River Basin in the Nebraska Panhandle has been designated as fully appropriated or overappropriated by the Nebraska Department of Natural Resources (NDNR). Enacted legislation (Legislative Bill 962) requires the North Platte Natural Resources District (NPNRD) and the NDNR to develop an Integrated Management Plan (IMP) to balance groundwater and surface-water supply and demand in the NPNRD. A clear understanding of the groundwater and surface-water systems is critical for the development of a successful IMP. The primary source of groundwater recharge in parts of the NPNRD is from irrigation canal leakage. Because canal leakage constitutes a large part of the hydrologic budget, spatially distributing canal leakage to the groundwater system is important to any management strategy. Surface geophysical data collected along selected reaches of irrigation canals has allowed for the spatial distribution of leakage on a relative basis; however, the actual magnitude of leakage remains poorly defined. To address this need, the U.S. Geological Survey, in cooperation with the NPNRD, established streamflow-gaging stations at upstream and downstream ends from two selected canal reaches to allow a mass-balance approach to be used to calculate daily leakage rates. Water-level and sediment temperature data were collected and simulated at three temperature monitoring sites to allow the use of heat as a tracer to estimate the hydraulic conductivity of canal bed sediment. Canal-leakage rates were estimated by applying Darcy's Law to modeled vertical hydraulic conductivity and either the estimated or measured hydraulic gradient. This approach will improve the understanding of the spatial and temporal variability of canal leakage in varying geologic settings identified in capacitively coupled resistivity surveys. The high-leakage potential study reach of the Tri-State Canal had two streamflow-gaging stations and two temperature monitoring sites along its length. Calculated leakage rates from the mass-balance approach varied from year to year and were generally dependent on local climatic conditions, and the timing and magnitude of the initial seasonal diversion into the Tri-State Canal. Leakage rates ranged from 0.98 meter per day (m/d) on June 22, 2007, to about to 0 m/d during July 2009. Drier conditions generally resulted in higher leakage rates because of reduced flow from Spottedtail Creek, lower groundwater levels near Spottedtail Creek, and no unmeasured flow entering the reach. Of the three years studied (2007-09), 2007 was the driest, and therefore had the highest canal leakage rates. The moderately low leakage potential study reach of Interstate Canal had two streamflow-gaging stations and one temperature monitoring site along its length. Excluding the leakage calculations from early May 2007, leakage rates ranged from 0.08 to 0.7 m/d. Less variability in leakage from year to year indicates that climatic conditions may have less of an effect for Interstate Canal compared to Tri-State Canal. This may be because Interstate Canal was cut into the northern edge of the North Platte alluvial valley and consequently the canal bed is well above the local groundwater table resulting in a constant (1 meter per meter [m/m]) hydraulic gradient. Interstate Canal also does not receive any captured flow that can vary substantially year to year. Two temperature monitoring sites were installed within the high-leakage potential reach of Tri-State Canal. Site TCTEMP1 was established in 2007 where the water table was well below the canal bed surface. The vertical hydraulic conductivity of the poorly sorted sand and gravel beneath site TCTEMP1 was estimated using a calibrated one-dimensional VS2DH model. Using a trial-and-error approach, the best-fit vertical hydraulic conductivity for the site TCTEMP1 model domain was 1.1 m/d. Site TCTEMP2 was established at the mouth of Spottedtail Creek where a shallow

Scientific Investigations Report↗

USGS2011

Predicting lake trophic state by relating Secchi-disk transparency measurements to Landsat-satellite imagery for Michigan inland lakes, 2003-05 and 2007-08

Inland lakes are an important economic and environmental resource for Michigan. The U.S. Geological Survey and the Michigan Department of Natural Resources and Environment have been cooperatively monitoring the quality of selected lakes in Michigan through the Lake Water Quality Assessment program. Sampling for this program began in 2001; by 2010, 730 of Michigan’s 11,000 inland lakes are expected to have been sampled once. Volunteers coordinated by the Michigan Department of Natural Resources and Environment began sampling lakes in 1974 and continue to sample (in 2010) approximately 250 inland lakes each year through the Michigan Cooperative Lakes Monitoring Program. Despite these sampling efforts, it still is impossible to physically collect measurements for all Michigan inland lakes; however, Landsat-satellite imagery has been used successfully in Minnesota, Wisconsin, Michigan, and elsewhere to predict the trophic state of unsampled inland lakes greater than 20 acres by producing regression equations relating in-place Secchi-disk measurements to Landsat bands. This study tested three alternatives to methods previously used in Michigan to improve results for predicted statewide Trophic State Index (TSI) computed from Secchi-disk transparency (TSI (SDT)). The alternative methods were used on 14 Landsat-satellite scenes with statewide TSI (SDT) for two time periods (2003– 05 and 2007–08). Specifically, the methods were (1) satellitedata processing techniques to remove areas affected by clouds, cloud shadows, haze, shoreline, and dense vegetation for inland lakes greater than 20 acres in Michigan; (2) comparison of the previous method for producing a single open-water predicted TSI (SDT) value (which was based on an area of interest (AOI) and lake-average approach) to an alternative Gethist method for identifying open-water areas in inland lakes (which follows the initial satellite-data processing and targets the darkest pixels, representing the deepest water, before regression equations are created); and (3) checking to see whether the predicted TSI (SDT) values compared well between two regression equations, one previously used in Michigan and an alternative equation from the hydrologic literature. The combination of improved satellite-data processing techniques and the Gethist method to identify open-water areas in inland lakes during 2003–05 and 2007–08 provided a stronger relation and statistical significance between predicted TSI (SDT) and measured TSI than did the AOI lake-average method; differences in results for the two methods were significant at the 99-percent confidence level. With regard to the comparison of the regression equations, there were no statistically significant differences at the 95-percent confidence level between results from the two equations. The previously used equation, in combination with the Gethist method, yielded coefficient of determination (R 2 ) values of 0.71 and 0.77 for the periods 2003–05 and 2007–08, respectively. The alternative equation, in combination with the Gethist method, yielded R 2 values of 0.74 and 0.75 for 2003–05 and 2007–08, respectively. Predicted TSI (SDT) and measured TSI (SDT) values for lakes used in the regression equations compared well, with R 2 values of 0.95 and 0.96 for predicted TSI (SDT) for 2003–05 and 2007–08, respectively. The R 2 values for statewide predicted TSI (SDT) for all inland lakes with available open-water areas for 2003–05 and 2007–08 were 0.91 and 0.93, respectively. Although the two equations predicted similar trophic-state classes, the alternative equation is planned to be used for future prediction of TSI (SDT) values for Michigan inland lakes, to promote consistency in comparing predicted values between States and for potential use in trend analysis.

Michigan↗

USGS2014

Resource manager information needs regarding hydrologic regime shifts for the North Pacific Landscape Conservation

Landscape Conservation Cooperatives (LCCs) are a network of 22 public-private partnerships, defined by ecoregion, that share and provide science to ensure the sustainability of land, water, wildlife, and cultural resources in North America. LCCs were established by the U.S. Department of the Interior (DOI) in recognition of the fact that response to climate change must be coordinated on a landscape-level basis because important resources, ecosystem processes, and resource management challenges extend beyond most of the boundaries considered in current natural resource management. The North Pacific LCC (NPLCC) covers the range of the Pacific coastal temperate rainforest, including an area of 528,360 km 2 spanning 22 degrees of latitude from the Kenai Peninsula, Alaska, to Bodega Bay, California. The coverage area includes parts of four States, two Canadian provinces, and more than 100 Tribes and First Nation language groups. It extends from alpine areas at the crest of coastal mountains across subalpine, montane, and lowland forests to the nearshore marine environment. This wide range of latitudes and elevation zones; terrestrial, freshwater, and marine habitats; and complex jurisdictional boundaries hosts a diversity of natural resources and their corresponding management issues are equally diverse. As evidenced by the Science and Traditional Ecological Knowledge (S-TEK) Strategy guiding principles, identifying and responding to the needs of resource managers is key to the success of the NPLCC. To help achieve this goal of the NPLCC, the U.S. Geological Survey (USGS) has organized several workshops with resource managers and resource scientists to identify management information needs relevant to the priority topics identified in the S-TEK Strategy. Here, we detail the results from a first workshop to address the effects of changes in hydrologic regime on rivers, streams, and riparian corridors. The workshop focused on a subset of the full NPLCC geography and was structured to answer the following questions: What are the valued resources and services that may be affected by hydrologic regime changes in the region? What are the management goals for those resources? How is climate change anticipated to affect valued resources and goals? What adaptation strategies may managers use in response to anticipated changes in resources due to climate-related hydrologic change? What information is needed to inform and use management responses?

Open-File Report↗

USGS2001

Energy resources and changing land use, Front Range of Colorado: AAPG-EMD field trip guide, in association with the 2001 AAPG-EMD annual meeting

Over the past 30 years, communities in the Northern Front Range of Colorado have experienced tremendous urban and commercial growth rivaling or surpassing that in most other parts of the United States. Much of this growth coincides with areas underlain by critically needed natural resources (such as oil, natural gas, construction aggregate (stone, sand, and gravel), and water), thus presenting serious challenges for city, county, and state planners as well as producers of these natural resources. With projections for as much as a 51 percent increase in population in Colorado over the next 25 years (Colorado Department of Local Affairs, 2001), it is likely that these challenges will increase. This field trip will blend petroleum and coal geology with discussions of urban development to highlight the interplay between growth in the Front Range and energy resource production. On the trip we will also explore the effects of past production on land use. A total of 6 stops will be made in various locations around the Front Range area.

Colorado↗