Geology topics

Tammy S. Fancher

Publications and source records attributed to Tammy S. Fancher.

12 recordsLinked to original sources

USGS2021

Compilation of information on occurrence and conservation status for the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma

The purpose of this data series is to compile information on the occurrence and conservation status of the freshwater mussel fauna of Nebraska, Kansas, and Oklahoma and to map the distribution of a freshwater mussel assemblage for the U.S. Department of the Interior, Bureau of Land Management Rapid Ecoregional Assessment (REA) program. The six focal species in the freshwater mussel assemblage are Amblema plicata ( threeridge), Fusconaia flava (Wabash pigtoe), Lampsilis cardium (plain pocketbook), Lampsilis teres (yellow sandshell), Pyganodon grandis (giant floater), and Uniomerus tetralasmus (pondhorn). The focal species were selected using the following criteria: (1) the species are regionally significant, (2) occurrence records are sufficient to map the distribution of the species by hydrologic subbasins, (3) the assemblage includes species representing a range of State-level conservation priorities, and (4) the species are not listed as federally endangered or threatened. In addition, the species represent a broad array of life history strategies and habitat associations. A total of 61 native species of freshwater mussels have documented occurrences within at least 1 of the 3 States, including 6 species that appear to have been extirpated from all the States and 6 species that may have been extirpated from at least 1 State. Of the 61 species, 8 species (including 3 potentially extirpated species) are listed as federally threatened or endangered and an additional 5 species are ranked as imperiled or vulnerable across their range. Approximately 80 percent of the native species known to have occurred within the three-State area have a secure conservation status, in comparison to only 40 percent of all freshwater mussel species or subspecies occurring within the United States. The compiled records for the contemporary period (1970–2017) documented the occurrence of 24 extant species in Nebraska, 42 in Kansas, and 48 in Oklahoma. The contemporary distributions of the six focal species were mapped by subbasins and the larger hydrologic subregions. Historical records (prior to 1962) were also mapped but were limited. Amblema plicata , Fusconaia flava , and Lampsilis cardium were present in approximately one-third of all subbasins and slightly more than half of the subregions, primarily along the eastern portion of the three-State area. Lampsilis teres and Uniomerus tetralasmus were more widespread, occurring in close to half of the subbasins and about three-quarters of the subregions. Pyganodon grandis was the most widespread, occurring in about three-quarters of the subbasins and almost all subregions. There were very few subbasins with historical occurrences that lacked contemporary occurrences. The broad-scale distribution maps for the freshwater mussel assemblage presented with this report are intended to contribute baseline information for regional assessments, such as the Southern Great Plains Rapid Ecoregional Assessment. Despite the limitations of the available data, such baseline information can be useful for identifying data gaps, monitoring future trends, identifying conservation priorities, and providing the larger context for more detailed watershed- or catchment-level studies. ScienceBase data release files associated with this data series are available at https://doi.org/10.5066/P9SBFZJU (Fancher and Carr, 2021).

Kansas, Nebraska, Oklahoma↗

USGS2014

Large scale Wyoming transportation data: a resource planning tool

The U.S. Geological Survey Fort Collins Science Center created statewide roads data for the Bureau of Land Management Wyoming State Office using 2009 aerial photography from the National Agriculture Imagery Program. The updated roads data resolves known concerns of omission, commission, and inconsistent representation of map scale, attribution, and ground reference dates which were present in the original source data. To ensure a systematic and repeatable approach of capturing roads on the landscape using on-screen digitizing from true color National Agriculture Imagery Program imagery, we developed a photogrammetry key and quality assurance/quality control protocols. Therefore, the updated statewide roads data will support the Bureau of Land Management’s resource management requirements with a standardized map product representing 2009 ground conditions. The updated Geographic Information System roads data set product, represented at 1:4,000 and +/- 10 meters spatial accuracy, contains 425,275 kilometers within eight attribute classes. The quality control of these products indicated a 97.7 percent accuracy of aspatial information and 98.0 percent accuracy of spatial locations. Approximately 48 percent of the updated roads data was corrected for spatial errors of greater than 1 meter relative to the pre-existing road data. Twenty-six percent of the updated roads involved correcting spatial errors of greater than 5 meters and 17 percent of the updated roads involved correcting spatial errors of greater than 9 meters. The Bureau of Land Management, other land managers, and researchers can use these new statewide roads data set products to support important studies and management decisions regarding land use changes, transportation and planning needs, transportation safety, wildlife applications, and other studies.

Wyoming↗

USGS2014

Spatial mapping and attribution of Wyoming wind turbines, 2012

These data represent locations of wind turbines found within Wyoming as of August 2012. We assigned each wind turbine to a wind farm and, in these data, provide information about each turbine’s potential megawatt output, rotor diameter, hub height, rotor height, the status of the land ownership where the turbine exists, the county each turbine is located in, wind farm power capacity, the number of units currently associated with each wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some of the attributes are estimates based on the information we found via the American Wind Energy Association and other on-line reports. The locations are derived from National Agriculture Imagery Program (2009 and 2012) true color aerial photographs and have a positional accuracy of approximately +/-5 meters. These data will provide a planning tool for wildlife- and habitat-related projects underway at the U.S. Geological Survey’s Fort Collins Science Center and other government and non-government organizations. Specifically, we will use these data to support quantifying disturbances of the landscape as related to wind energy as well as to quantify indirect disturbances to flora and fauna. This data set represents an update to a previous version by O’Donnell and Fancher (2010).

Wyoming↗

USGS2013

Locations and attributes of wind turbines in Colorado, 2011

This dataset represents an update to U.S. Geological Survey Data Series 597. Locations and attributes of wind turbines in Colorado, 2009 (available at http://pubs.usgs.gov/ds/597/). This updated Colorado wind turbine Data Series provides geospatial data for all 1,204 wind turbines established within the State of Colorado as of September 2011, an increase of 297 wind turbines from 2009. Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, county, and development status of the wind turbine. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, and year the facility went online. The locations of turbines are derived from 1-meter true-color aerial photographs produced by the National Agriculture Imagery Program (NAIP); the photographs have a positional accuracy of about ±5 meters. Locations of turbines constructed during or prior to August 2009 are based on August 2009 NAIP imagery and turbine locations constructed after August 2009 were based on September 2011 NAIP imagery. The location of turbines under construction during September 2011 likely will be less accurate than the location of existing turbines. This data series contributes to an Online Interactive Energy Atlas developed by the U.S. Geological Survey (http://my.usgs.gov/eerma/). The Energy Atlas synthesizes data on existing and potential energy development in Colorado and New Mexico and includes additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools also are included in the Energy Atlas. The format of the Energy Atlas is designed to facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.

Colorado↗

USGS2013

Locations and attributes of wind turbines in New Mexico, 2011

This dataset represents an update to U.S. Geological Survey Data Series 596. Locations and attributes of wind turbines in New Mexico, 2009 (available at http://pubs.usgs.gov/ds/596/).This updated New Mexico wind turbine Data Series provides geospatial data for all 562 wind turbines established within the State of New Mexico as of June 2011, an increase of 155 wind turbines from 2009. Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, county, and development status of wind turbine. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, and year the facility went online. The locations of turbines are derived from 1-meter true-color aerial photographs produced by the National Agriculture Imagery Program (NAIP); the photographs have a positional accuracy of about ±5 meters. The locations of turbines constructed during or prior to August 2009 are based on August 2009 NAIP imagery and turbine locations constructed after August 2009 were based June 2011 NAIP imagery. The location of turbines under construction during June 2011 likely will be less accurate than the location of existing turbines. This data series contributes to an Online Interactive Energy Atlas developed by the U.S. Geological Survey (http://my.usgs.gov/eerma/). The Energy Atlas synthesizes data on existing and potential energy development in Colorado and New Mexico and includes additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools also are included in the Energy Atlas. The format of the Energy Atlas is designed to facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.

New Mexico↗

USGS2012

Mapping surface disturbance of energy-related infrastructure in southwest Wyoming--An assessment of methods

We evaluated how well three leading information-extraction software programs (eCognition, Feature Analyst, Feature Extraction) and manual hand digitization interpreted information from remotely sensed imagery of a visually complex gas field in Wyoming. Specifically, we compared how each mapped the area of and classified the disturbance features present on each of three remotely sensed images, including 30-meter-resolution Landsat, 10-meter-resolution SPOT (Satellite Pour l'Observation de la Terre), and 0.6-meter resolution pan-sharpened QuickBird scenes. Feature Extraction mapped the spatial area of disturbance features most accurately on the Landsat and QuickBird imagery, while hand digitization was most accurate on the SPOT imagery. Footprint non-overlap error was smallest on the Feature Analyst map of the Landsat imagery, the hand digitization map of the SPOT imagery, and the Feature Extraction map of the QuickBird imagery. When evaluating feature classification success against a set of ground-truthed control points, Feature Analyst, Feature Extraction, and hand digitization classified features with similar success on the QuickBird and SPOT imagery, while eCognition classified features poorly relative to the other methods. All maps derived from Landsat imagery classified disturbance features poorly. Using the hand digitized QuickBird data as a reference and making pixel-by-pixel comparisons, Feature Extraction classified features best overall on the QuickBird imagery, and Feature Analyst classified features best overall on the SPOT and Landsat imagery. Based on the entire suite of tasks we evaluated, Feature Extraction performed best overall on the Landsat and QuickBird imagery, while hand digitization performed best overall on the SPOT imagery, and eCognition performed worst overall on all three images. Error rates for both area measurements and feature classification were prohibitively high on Landsat imagery, while QuickBird was time and cost prohibitive for mapping large spatial extents. The SPOT imagery produced map products that were far more accurate than Landsat and did so at a far lower cost than QuickBird imagery. Consideration of degree of map accuracy required, costs associated with image acquisition, software, operator and computation time, and tradeoffs in the form of spatial extent versus resolution should all be considered when evaluating which combination of imagery and information-extraction method might best serve any given land use mapping project. When resources permit, attaining imagery that supports the highest classification and measurement accuracy possible is recommended.

Wyoming↗

USGS2011

Locations and attributes of wind turbines in New Mexico, 2009

The New Mexico wind-turbine data series provides geospatial data for all wind turbines established within the State as of August 2009. Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, and county. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, year the facility went online, and development status of wind facility. Turbine locations were derived from 1-meter August 2009 true-color aerial photographs produced by the National Agriculture Imagery Program; the photographs have a positional accuracy of about + or - 5 meters. The location of turbines under construction during August 2009 likely will be less accurate than the location of existing turbines. This data series contributes to an Online Interactive Energy Atlas currently (2011) in development by the U.S. Geological Survey. The Energy Atlas will synthesize data on existing and potential energy development in Colorado and New Mexico and will include additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools will be included in the Energy Atlas. The format of the Energy Atlas will facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.

Data Series↗

USGS2011

Locations and attributes of wind turbines in Colorado, 2009

The Colorado wind-turbine data series provides geospatial data for all wind turbines established within the State as of August 2009. Attributes specific to each turbine include: turbine location, manufacturer and model, rotor diameter, hub height, rotor height, potential megawatt output, land ownership, and county. Wind energy facility data for each turbine include: facility name, facility power capacity, number of turbines associated with each facility to date, facility developer, facility ownership, year the facility went online, and development status of wind facility. Turbine locations were derived from August 2009 1-meter true-color aerial photographs produced by the National Agriculture Imagery Program; the photographs have a positional accuracy of about + or - 5 meters. The location of turbines under construction during August 2009 likely will be less accurate than the location of existing turbines. This data series contributes to an Online Interactive Energy Atlas currently (2011) in development by the U.S. Geological Survey. The Energy Atlas will synthesize data on existing and potential energy development in Colorado and New Mexico and will include additional natural resource data layers. This information may be used by decisionmakers to evaluate and compare the potential benefits and tradeoffs associated with different energy development strategies or scenarios. Interactive maps, downloadable data layers, comprehensive metadata, and decision-support tools will be included in the Energy Atlas. The format of the Energy Atlas will facilitate the integration of information about energy with key terrestrial and aquatic resources for evaluating resource values and minimizing risks from energy development.

Data Series↗

USGS2010

Spatial mapping and attribution of Wyoming wind turbines

This Wyoming wind-turbine data set represents locations of wind turbines found within Wyoming as of August 1, 2009. Each wind turbine is assigned to a wind farm. For each turbine, this report contains information about the following: potential megawatt output, rotor diameter, hub height, rotor height, land ownership, county, wind farm power capacity, the number of units currently associated with its wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some attributes are estimates based on information that was obtained through the American Wind Energy Association and miscellaneous online reports. The locations are derived from August 2009 true-color aerial photographs made by the National Agriculture Imagery Program; the photographs have a positional accuracy of approximately ?5 meters. The location of wind turbines under construction during the development of this data set will likely be less accurate than the location of turbines already completed. The original purpose for developing the data presented here was to evaluate the effect of wind energy development on seasonal habitat used by greater sage-grouse. Additionally, these data will provide a planning tool for the Wyoming Landscape Conservation Initiative Science Team and for other wildlife- and habitat-related projects underway at the U.S. Geological Survey's Fort Collins Science Center. Specifically, these data will be used to quantify disturbance of the landscape related to wind energy as well as quantifying indirect disturbances to flora and fauna. This data set was developed for the 2010 project 'Seasonal predictive habitat models for greater sage-grouse in Wyoming.' This project's spatially explicit seasonal distribution models of sage-grouse in Wyoming will provide resource managers with tools for conservation planning. These specific data are being used for assessing the effect of disturbance resulting from wind energy development within Wyoming on sage-grouse populations.

Data Series↗

USGS2010

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗

USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗

USGS2007

Environmental effects of off-highway vehicles on Bureau of Land Management lands: A literature synthesis, annotated bibliographies, extensive bibliographies, and internet resources

This report and its associated appendixes compile and synthesize the results of a comprehensive literature and Internet search conducted in May 2006. The literature search was undertaken to uncover information regarding the effects of off-highway vehicle (OHV) use on land health, or “natural resource attributes,” and included databases archiving information from before OHVs came into existence to May 2006. Information pertaining to socioeconomic implications of OHV activities is included as well. The literature and Internet searches yielded approximately 700 peer-reviewed papers, magazine articles, agency and non-governmental reports, and internet websites regarding effects of OHV use as they relate to the Bureau of Land Management’s (BLM) standards of land health. Discussions regarding OHV effects are followed by brief syntheses of potential indicators of OHV effects, as well as OHV-effects mitigation, site-restoration techniques, and research needs.

Open-File Report↗