Ecological implications of geopressured-geothermal energy development: Texas-Louisiana Gulf Coast region
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FWS/OBS↗
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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.
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Summary plan for application of coastal characterizations to energy-related developments
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FWS/OBS↗
Energy related use conflicts for the Columbia River estuary
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FWS/OBS↗
Human demographic impacts on fish and wildlife resources from energy development in rural western areas
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FWS/OBS↗
Ice ages and the thermal equilibrium of the earth, II
The energy required to sustain midlatitude continental glaciations comes from solar radiation absorbed by the oceans. It is made available through changes in relative amounts of energy lost from the sea surface as net outgoing infrared radiation, sensible heat loss, and latent heat loss. Ice sheets form in response to the initial occurrence of a large perennial snowfield in the subarctic. When such a snowfield forms, it undergoes a drastic reduction in absorbed solar energy because of its high albedo. When the absorbed solar energy cannot supply local infrared radiation losses, the snowfield cools, thus increasing the energy gradient between itself and external, warmer areas that can act as energy sources. Cooling of the snowfield progresses until the energy gradients between the snowfield and external heat sources are sufficient to bring in enough (latent plus sensible) energy to balance the energy budget over the snowfield. Much of the energy is imported as latent heat. The snow that falls and nourishes the ice sheet is a by-product of the process used to satisfy the energy balance requirements of the snowfield. The oceans are the primary energy source for the ice sheet because only the ocean can supply large amounts of latent heat. At first, some of the energy extracted by the ice sheet from the ocean is stored heat, so the ocean cools. As it cools, less energy is lost as net outgoing infrared radiation, and the energy thus saved is then available to augment evaporation. The ratio between sensible and latent heat lost by the ocean is the Bowen ratio; it depends in part on the sea surface temperature. As the sea surface temperature falls during a glaciation, the Bowen ratio increases, until most of the available energy leaves the oceans as sensible, rather than latent heat. The ice sheet starves, and an interglacial period begins. The oscillations between stadial and interstadial intervals within a glaciation are caused by the effects of varying amounts of glacial meltwater entering the oceans as a surface layer that acts to reduce the amount of energy available for glacial nourishment. This causes the ice sheet to melt back, which continues the supply of meltwater until the ice sheet diminishes to a size consistent with the reduced rate of nourishment. The meltwater supply then decreases, the rate of nourishment increases, and a new stadial begins.
Quaternary Research↗
Evapotranspiration from areas of native vegetation in west-central Florida
A study was conducted to evaluate the suitability of three micrometeorological methods for estimating evapotranspiration from selected areas of native vegetation in west-central Florida and to estimate annual evapotranspiration from areas having a specific vegetation type. Evapotranspiration was estimated using the methods of energy-balance Bowen ratio (EBBR) and eddy correlation. Potential evapotranspiration was computed using the Penman equation. Field measurements were made intermittently from February 1988 through September 1990. The EBBR method was used to estimate evapotranspiration from unforested and forested sites. A mean-gradient Bowen ratio system was used to measure and average vertical air temperature and vapor-pressure gradients, and the Bowen ratio was computed using the mean air temperature and vapor-pressure gradients. The Bowen ratio estimated in this manner was then used to compute evapotranspiration by the EBBR method. Computations that were based on objective review criteria indicated that the Bowen ratio that was computed using measurements that were made using the mean-gradient Bowen ratio system was not always realistic. During a period of extended operation at a dry prairie site, 9 percent of measured available energy during the daytime occurred when the Bowen ratio obtained using the mean-gradient Bowen ratio system was unrealistic. During 5 out of 14 days of continuous operation at a marsh site, more than 30 percent of measured available energy during the daytime occurred when the Bowen ratio obtained using the mean-gradient Bowen ratio system was unrealistic. One of the primary causes of unrealistic Bowen ratios at the unforested sites was condensation of moisture within the tubing of the mean-gradient Bowen ratio system. Measurements made using the mean-gradient Bowen ratio system at a forested pine flatwood site indicated that vapor-pressure gradients were too weak to be resolved by the system. As a result, the Bowen ratio computed for the forested sites was unreliable when it was obtained using the mean-gradient Bowen ratio system. Direct estimates of sensible and latent heat flux that were computed from eddy correlation measurements were generally insufficient to account for measured available energy at all sites. Analysis of eddy correlation and energy-balance data indicated that the sum of sensible and latent heat fluxes accounted for 68 percent of available energy at dry prairie and marsh sites, 74 percent of available energy at a pine flatwood site, and 45 percent of available energy at a cypress swamp site. Because specific causes of the energy-balance discrepancies could not be quantified, corrections to the direct eddy correlation flux estimates could not be made, and eddy correlation data were combined with other energy-balance data to yield two alternative evapotranspiration estimates. The first alternative evapotranspiration estimate was computed by combining sensible heat flux obtained from eddy correlation with measurements of available energy to compute latent heat flux as the residual of the equation for the surface energy balance. The second alternative evapotranspiration estimate was computed by using direct sensible and latent heat flux estimates that were obtained from eddy correlation measurements to compute the Bowen ratio. The Bowen ratio obtained from eddy correlation measurements was then combined with measurements of available energy to compute evapotranspiration by the EBBR method. Of the three alternative evapotranspiration estimates that were obtained from eddy correlation measurements, the estimate that was computed using the EBBR method, with the Bowen ratio computed from eddy correlation measurements, agreed most strongly with the corresponding evapotranspiration estimate that was computed using the EBBR method with the Bowen ratio obtained from the mean-gradient Bowen ratio system. It is probable that actual evapo-transpiration was within a range defined by the standard eddy correlation computation, which consistently indicated the smallest evapotranspiration, and the energy-balance residual computation, which consistently indicated the largest evapotranspiration. Daily potential evapotranspiration, as computed by the Penman method, and daily evapotranspiration, as computed by the EBBR method, did not seem to correlate with each other at a dry prairie site during late spring and summer; however, the two were correlated with each other at a marsh site during late spring and summer. Evapotranspiration was approximately 57 percent of potential evapotranspiration at the marsh site. The correlation between evapotranspiration and potential evapotranspiration at the marsh site, and the fact that evapotranspiration approached potential evapotranspiration, indicated that the Penman method can be useful for estimating evapotranspiration from marshes in west-central Florida. Annual evapotranspiration estimates were developed for each vegetation type by pooling EBBR and eddy correlation measurements among sites and among the 3 years during which field measurements were made. Three different estimates, which correspond to the three eddy correlation computation methods, were made for each vegetation type. The centric estimates, which were calculated by using the EBBR method with the Bowen ratio obtained from either a mean-gradient system or from eddy correlation measurements, were 1,010 millimeters per year for the dry prairie type, 990 millimeters per year for the marsh vegetation type, 1,060 millimeters per year for the pine flatwood type, and 970 millimeters per year for the cypress swamp type.
Florida↗
Entropy, materials, and posterity
Materials and energy are the interdependent feedstocks of economic systems, and thermodynamics is their moderator. It costs energy to transform the dispersed minerals of Earth's crust into ordered materials and structures. And it costs materials to collect and focus the energy to perform work - be it from solar, fossil fuel, nuclear, or other sources. The greater the dispersal of minerals sought, the more energy is required to collect them into ordered states. But available energy can be used once only. And the ordered materials of industrial economies become disordered with time. They may be partially reordered and recycled, but only at further costs in energy. Available energy everywhere degrades to bound states and order to disorder - for though entropy may be juggled it always increases. Yet industry is utterly dependent on low entropy states of matter and energy, while decreasing grades of ore require ever higher inputs of energy to convert them to metals, with ever increasing growth both of entropy and environmental hazard. Except as we may prize a thing for its intrinsic qualities - beauty, leisure, love, or gold - low-entropy is the only thing of real value. It is worth whatever the market will bear, and it becomes more valuable as entropy increases. It would be foolish of suppliers to sell it more cheaply or in larger amounts than their own enjoyment of life requires, whatever form it may take. For this reason, and because of physical constraints on the availability of all low-entropy states, the recent energy crises is only the first of a sequence of crises to be expected in energy and materials as long as current trends continue. The apportioning of low-entropy states in a modern industrial society is achieved more or less according to the theory of competitive markets. But the rational powers of this theory suffer as the world grows increasingly polarized into rich, over-industrialized nations with diminishing resource bases and poor, supplier nations with little industry. The theory also discounts posterity, the more so as population density and percapita rates of consumption continue to grow. A new social, economic, and ecologic norm that leads to population control, conservation, and an apportionment of low-entropy states across the generations is needed to assure to posterity the options that properly belong to it as an important but voiceless constituency of the collectivity we call mankind. ?? 1977 Ferdinand Enke Verlag Stuttgart.
Geologische Rundschau↗
Less waste corn, more land in soybeans, and the switch to genetically modified crops: Trends with important implications for wildlife management
American agriculture has provided abundant high-energy foods for migratory and resident wildlife populations since the onset of modern wildlife management. Responding to anecdotal evidence that corn residues are declining in cropland, we remeasured waste corn post-harvest in the Central Platte River Valley (CPRV) of Nebraska during 1997 and 1998 to compare with 1978. Post-harvest waste corn averaged 2.6% and 1.8% of yield in 1997 and 1998, respectively. After accounting for a 20% increase in yield, waste corn in 1997 and 1998 was reduced 24% and 47% from 1978. We also evaluated use of soybeans by spring-staging sandhill cranes ( Crus canadensis ) and waterfowl during spring 1998 and 1999. Despite being widely available in the CPRV, soybeans did not occur in esophageal contents of sandhill cranes ( n= 174), northern pintails ( Anas acuta , n= 139), greater white-fronted geese ( Anser albifrons , n= 198), or lesser snow geese ( Chen caerulescens , n= 208) collected with food in their esophagi. Lack of soybean consumption by cranes and waterfowl in Nebraska in early spring builds upon previously published findings, suggesting that soybeans are poorly suited for meeting nutrient needs of wildlife requiring a high-energy diet. Given evidence that high-energy food and numerous populations of seed-eating species found on farmland are declining, and the enormous potential risk to game and nongame wildlife populations if high-energy foods were to become scarce, a comprehensive research effort to study the problem appears warranted. Provisions under the Conservation Security subtitle of The Farm Security and Rural Investment Act of 2002 offer a potential mechanism to encourage producers to manage cropland in ways that would replace part of the high-energy foods that have been lost to increasing efficiency of production agriculture.
Nebraska↗
Mortality monitoring design for utility-scale solar power facilities
Introduction Solar power represents an important and rapidly expanding component of the renewable energy portfolio of the United States (Lovich and Ennen, 2011; Hernandez and others, 2014). Understanding the impacts of renewable energy development on wildlife is a priority for the U.S. Fish and Wildlife Service (FWS) in compliance with Department of Interior Order No. 3285 (U.S. Department of the Interior, 2009) to “develop best management practices for renewable energy and transmission projects on the public lands to ensure the most environmentally responsible development and delivery of renewable energy.” Recent studies examining effects of renewable energy development on mortality of migratory birds have primarily focused on wind energy (California Energy Commission and California Department of Fish and Game, 2007), and in 2012 the FWS published guidance for addressing wildlife conservation concerns at all stages of land-based wind energy development (U.S. Fish and Wildlife Service, 2012). As yet, no similar guidelines exist for solar development, and no published studies have directly addressed the methodology needed to accurately estimate mortality of birds and bats at solar facilities. In the absence of such guidelines, ad hoc methodologies applied to solar energy projects may lead to estimates of wildlife mortality rates that are insufficiently accurate and precise to meaningfully inform conversations regarding unintended consequences of this energy source and management decisions to mitigate impacts. Although significant advances in monitoring protocols for wind facilities have been made in recent years, there remains a need to provide consistent guidance and study design to quantify mortality of bats, and resident and migrating birds at solar power facilities (Walston and others, 2015). In this document, we suggest methods for mortality monitoring at solar facilities that are based on current methods used at wind power facilities but adapted for the unique conditions encountered at solar facilities. In particular, unlike at wind-power facilities, the unimpeded access to almost all areas within the facilities, the typically flat terrain, and general absence of thick vegetation allow distance-sampling techniques (Buckland and others, 2001, 2004) to be exploited to advantage at industrial solar sites. These protocols build on the work of Nicolai and others (2011), and as our understanding and techniques for monitoring improve, the methods may be further modified to incorporate improvements in the future. We present case studies based on monitoring methods currently implemented at different utility-scale solar facilities to illustrate how distance-sampling techniques may improve overall detectability without substantially increasing costs. Every facility is unique, and the protocols presented may be adapted based on specific monitoring objectives and conditions at each site. We provide guidance for designing monitoring programs whose objective it is to estimate the total number of bird and bat fatalities occurring at a facility over an extended period of time. We address spatial variation in causes of mortality, as well as potential sources of imperfect detection, for example, animals falling in or moving to unsearched areas, carcasses removed by predators, and carcasses missed by searchers. We suggest methods to estimate and account for each source of imperfect detection. This document focuses on monitoring design only and does not discuss approaches for estimating mortality from collected data. The development of statistically sound estimators relevant to the solar context is a current topic of research, although there are already strong foundations for estimation with distance-sampling methods in similar open, arid environments (Anderson and others, 2001; Freilich and others, 2005). Nonetheless, if protocols described in this document are followed, the resulting data will be adequate and sufficient for estimating mortality using newly formulated estimators.
Open-File Report↗
Evaporation from Lake Mead, Nevada and Arizona, March 2010 through February 2012
Evaporation from Lake Mead was measured using the eddy-covariance method for the 2-year period starting March 2010 and ending February 2012. When corrected for energy imbalances, annual eddy-covariance evaporation was 2,074 and 1,881 millimeters (81.65 and 74.07 inches), within the range of previous estimates. There was a 9-percent decrease in the evaporation rate and a 10-percent increase in the lake surface area during the second year of the study compared to the first. These offsetting factors resulted in a nearly identical 720 million cubic meters (584,000 acre feet) evaporation volume for both years. Monthly evaporation rates were best correlated with wind speed, vapor pressure difference, and atmospheric stability. Differences between individual monthly evaporation and mean monthly evaporation were as much as 20 percent. Net radiation provided most of the energy available for evaporative processes; however, advected heat from the Colorado River was an important energy source during the second year of the study. Peak evaporation lagged peak net radiation by 2 months because a larger proportion of the net radiation that reaches the lake goes to heating up the water column during the spring and summer months. As most of this stored energy is released, higher evaporation rates are sustained during fall months even though net radiation declines. The release of stored heat also fueled nighttime evaporation, which accounted for 37 percent of total evaporation. The annual energy-balance ratio was 0.90 on average and varied only 0.01 between the 2 years, thus implying that 90 percent of estimated available energy was accounted for by turbulent energy measured using the eddy-covariance method. More than 90 percent of the turbulent-flux source area represented the open-water surface, and 94 percent of 30-minute turbulent-flux measurements originated from wind directions where the fetch ranged from 2,000 to 16,000 meters. Evaporation uncertainties were estimated to be 5 to 7 percent. A secondary evaporation method, the Bowen ratio energy budget method, also was employed to measure evaporation from Lake Mead primarily as a validation of eddy-covariance evaporation measurements at annual timescales. There was good agreement between annual corrected eddy-covariance and Bowen ratio energy budget evaporation estimates, providing strong validation of these two largely independent methods. Annual Bowen ratio energy budget evaporation was 6 and 8 percent greater than eddy-covariance evaporation for the 2 study years, and both methods indicated there was a similar decrease in evaporation from the first to the second year. Both methods produced negative sensible heat fluxes during the same months, and there was a strong correlation between monthly Bowen ratios (R 2 = 0.94). The correlation between monthly evaporation (R 2 = 0.65), however, was not as strong. Monthly differences in evaporation were attributed primarily to heat storage estimate uncertainty.
Arizona;Nevada↗
Regional evaluation of evapotranspiration in the Everglades
Nine sites in the Florida Everglades were selected and instrumented for collection of data necessary for evapotranspiration-determination using the Bowen-ratio energy-budget method. The sites were selected to represent the sawgrass or cattail marshes, wet prairie, and open-water areas that constitute most of the natural Everglades system. At each site, measurements necessary for evapotranspiration (ET) calculation and modeling were automatically made and stored on-site at 15- or 30-minute intervals. Data collected included air temperature and humidity at two heights, wind speed and direction, incoming solar radiation, net solar radiation, water level and temperature, soil moisture content, soil temperature, soil heat flux, and rainfall. Data summarized in this report were collected from January 1996 through December 1997, and the development of site-specific and regional models of ET for this period is described. Latent heat flux is the energy flux density equivalent of the ET rate. Modified Priestley-Taylor models of latent heat flux as a function of selected independent variables were developed at each site. These models were used to fill in periods of missing latent heat flux measurement, and to develop regional models of the entire Everglades region. The regional models may be used to estimate ET in wet prairie, sawgrass or cattail marsh, and open-water portions of the natural Everglades system. The models are not applicable to forested areas or to the brackish areas adjacent to Florida Bay. Two types of regional models were developed. One type of model uses measurements of available energy at a site, together with incoming solar energy and water depth, to estimate hourly ET. This available-energy model requires site data for net radiation, water heat storage, and soil heat flux, as well as data for incoming solar radiation and water depth. The other type of model requires only incoming solar energy, air temperature, and water depth data to provide estimates of hourly ET. The second model thus uses data that are more readily available than the data required for the available-energy model. Computed ET mean annual totals for all nine sites for the 1996-97 period ranged from 42.4 inches per year at a site where the water level is below land surface for several months each year to 57.4 inches per year at an open-water site with no emergent vegetation. Although the density of photosynthetically-active plant leaves has been shown to relate directly to ET in some studies, it does not appear to relate directly to ET in the Everglades, based on comparison of annual ET data with leaf-area index, defined as the Normalized Difference Vegetation Index (NDVI), data from satellite imagery. NDVI and ET appear to be inversely related in the Everglades. The greatest ET rates occurred at open-water sites where the NDVI data indicated the lowest leaf-area index. Among the remaining vegetated sites, there is no clear relation between ET and NDVI, though the highest ET rate corresponded to the lowest NDVI and one of the lowest ET rates corresponded to the highest NDVI value. The variation in ET follows a seasonal pattern, with lowest monthly ET totals occurring in December through February, and highest ET occurring in May through August. The greatest range in monthly ET among all nine sites for the 2-year period occurred at site 3: from 1.81 inches in December 1997 to 6.84 inches in July 1996. A study to compare the Bowen-ratio/energy balance method of ET measurement with the eddy-correlation method was done at one site from June 22, 1998, through September 28, 1998. This comparison indicated that both methods gave comparable values of the Bowen ratio, but there was a considerable difference in available energy measured by the two methods. The mean of all 30-minute measured turbulent heat fluxes from the eddy-correlation apparatus for June 22 through September 29, 1998, was 137.4 watts per square meter, and the mean of the corresponding measured energy was 163.6 watts per square meter, or about 20 percent greater. The disagreement in mean energy fluxes measured by the two methods is problematical and is not fully understood. Although the difference seems to be related to friction velocity, and is practically non-existent at values of friction velocity greater than 0.3 meter per second, the "correctness" of either method cannot be determined with the data available.
Florida↗
Testing food web theory in a large lake: The role of body size in habitat coupling in Lake Michigan
The landscape theory of food web architecture (LTFWA) describes relationships among body size, trophic position, mobility, and energy channels that serve to couple heterogenous habitats, which in turn promotes long-term system stability. However, empirical tests of the LTFWA are rare and support differs among terrestrial, freshwater, and marine systems. Further, it is unclear whether the theory applies in highly altered ecosystems dominated by introduced species such as the Laurentian Great Lakes. Here, we provide an empirical test of the LTFWA by relating body size, trophic position, and the coupling of different energy channels using stable isotope data from species throughout the Lake Michigan food web. We found that body size was positively related to trophic position, but for a given trophic position, organisms predominately supported by pelagic energy had smaller body sizes than organisms predominately supported by nearshore benthic energy. We also found a hump-shaped trophic relationship in the food web where there is a gradual increase in the coupling of pelagic and nearshore energy channels with larger body sizes as well as higher trophic positions. This highlights the important role of body size and connectivity among habitats in structuring food webs. However, important deviations from expectations are suggestive of how species introductions and other anthropogenic impacts can affect food web structure in large lakes. First, native top predators appear to be flexible couplers that may provide food web resilience, whereas introduced top predators may confer less stability when they specialize on a single energy pathway. Second, some smaller bodied prey fish and invertebrates, in addition to mobile predators, coupled energy from pelagic and nearshore energy channels, which suggests that some prey species may also be important integrators of energy pathways in the system. We conclude that patterns predicted by the LTFWA are present in the face of species introductions and other anthropogenic stressors to a degree, but time-series evaluations are needed to fully understand the mechanisms that promote stability.
Lake Michigan↗
Spatial patterns of rainbow smelt energetic condition in Lakes Huron and Erie in 2017: Evidence for Lake Huron resource limitation
Rainbow smelt ( Osmerus mordax ) is a key planktivore and prey fish in Lake Huron. Given the declining offshore productivity in the lake since the early 2000s, we described the energy content of rainbow smelt in 2017 across five different regions (North Channel, Georgian Bay, Saginaw Bay, northern main basin, southern main basin) where phytoplankton and zooplankton productivity likely varied. To increase contrast across the productivity gradient, rainbow smelt energy content was also estimated from western Lake Erie. Within the North Channel where large fish (≥90 mm, total length) were sampled most frequently, mean energy density (kJ/g wet weight) varied seasonally: 4.29 in April (month of spawning), 3.86 in June, 3.99 in July, and up to 4.35 in September. Energy density of rainbow smelt from higher productivity western Lake Erie was 37% (large fish ≥90 mm) to 60% higher (small fish <90 mm) than that of fish from Lake Huron. Within Lake Huron, energy density of rainbow smelt from North Channel was slightly higher than those from other regions; rainbow smelt from Georgian Bay generally had the lowest energy density. Across regions, including western Lake Erie, energy density increased with chlorophyll a concentration. Compared with Lake Huron studies prior to 2004, when oligotrophication had not yet accelerated, energy density of rainbow smelt in 2017 was up to 31% lower. The decline in rainbow smelt energy density is likely the result of declining primary and secondary pelagic production and increased resource limitation for planktivorous fish.
Michigan, Ohio, Ontario↗
Population dynamics and bioenergetics of a fossorial herbivore, Thomomys talpoides (Rodentia: Geomyidae), in a spruce-fir sere
Studies of the bioenergetics of the northern pocket gopher, Thomomys talpoides , are coupled with data on demography, activity budgets, and microclimates to model the energy requirements of individuals and populations in the Wasatch Mountains of Utah during 1976-1979. Metabolic rates during rest increased linearly with decreasing ambient temperature, but burrowing metabolic rates (16.3 mL O 2 • h -1 • g -9.75 ) were independent of both temperature and physical properties of the soil. Radio-telemetry studies indicated that free-ranging gophers are active =50% of each day. Conservative estimates of true energy consumption were calculated using estimates of habitat-specific minimum daily burrowing requirements. Rates of burrowing measured in the laboratory were either ∞ 0.0 or ∞ 2.0 cm/min. The low burrowing rate was observed when the soil was frozen or saturated with water, as would occur in the field in early winter and in spring, respectively. Gophers burrowed through soil at the study site at an average rate of ∞ 1.5 cm/min. Belowground food energy densities at gopher foraging depth declined from 24.6 to 3.2 J/cm 3 along a successional gradient (subalpine forb meadow to Engelmann spruce dominated forest). We conclude that individual gophers are food limited within the climax spruce seral stage. Further, daily energy costs associated with reproduction in females may exceed the belowground energy supply available in intermediate seral stages (aspen and subalpine fir). Reduction of burrowing rates for any reason will affect gophers in the late seral stages proportionately more than those resident in the meadow. The peak gopher densities recorded (from 62 individuals/ha in the meadow to 2 individuals/ha in spruce forest) support these inferences. Detailed demographic information was obtained only in the meadow seral stage. Adult survivorship was lower in winter than in summer and varied greatly between years (0.18-0.70 yr -1 ). Juvenile survivorship from weaning through the first year was comparable to adult annual rates. The fertility rate was 3.75 young • female -1 • yr -1 . The energy supply and demand analyses indicate that the growth of Thomomys talpoides populations in the early seral stages is seldom directly limited by the amount of food present. From our demographic, environmental, and autecological studies we conclude that stochastic events associated with weather affect energy acquisition (burrowing) rates, and thus survivorship. In montane environments, such events may prevent populations from attaining sizes at which territorial behavior would hypothetically limit further increases. The energy flow through the meadow population at moderate to high )1976-1977) densities (at least 1100 MJ • ha -1 • yr -1 ) indicates that pocket gophers are proficient energy movers relative to non-fossorial small mammals. Subalpine T. talpoides populations appear commonly to attain such densities. More than 30% of the annual primary productivity allocated to belowground parts of meadow forbs may be consumed by gophers.
Ecological Monographs↗
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↗
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↗
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↗
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↗