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A table of the analytical sensitivities of the principal lines in the thermal neutron capture gamma-ray spectrum from 0 to 3 MeV has been compiled for most of the elements. A tabulation of the full-energy, single-escape, and double-escape peaks has also been made according to energy. The tables are useful for spectral interpretation and calibration.
In northern peatlands, subsurface ice formation is an important process that can control heat transport, groundwater flow, and biological activity. Temperature was measured over one and a half years in a vertical profile in the Red Lake Bog, Minnesota. To successfully simulate the transport of heat within the peat profile, the U.S. Geological Survey's SUTRA computer code was modified. The modified code simulates fully saturated, coupled porewater-energy transport, with freezing and melting porewater, and includes proportional heat capacity and thermal conductivity of water and ice, decreasing matrix permeability due to ice formation, and latent heat. The model is verified by correctly simulating the Lunardini analytical solution for ice formation in a porous medium with a mixed ice-water zone. The modified SUTRA model correctly simulates the temperature and ice distributions in the peat bog. Two possible benchmark problems for groundwater and energy transport with ice formation and melting are proposed that may be used by other researchers for code comparison.
Numerous cold regions water flow and energy transport models have emerged in recent years. Dissimilarities often exist in their mathematical formulations and/or numerical solution techniques, but few analytical solutions exist for benchmarking flow and energy transport models that include pore water phase change. This paper presents a detailed derivation of the Lunardini solution, an approximate analytical solution for predicting soil thawing subject to conduction, advection, and phase change. Fifteen thawing scenarios are examined by considering differences in porosity, surface temperature, Darcy velocity, and initial temperature. The accuracy of the Lunardini solution is shown to be proportional to the Stefan number. The analytical solution results obtained for soil thawing scenarios with water flow and advection are compared to those obtained from the finite element model SUTRA. Three problems, two involving the Lunardini solution and one involving the classic Neumann solution, are recommended as standard benchmarks for future model development and testing.
Surface energy exchanges were measured in a sequence of five sites representing the major vegetation types in the transition from arctic tundra to forest. This is the major transition in vegetation structure in northern high latitudes. We examined the influence of vegetation structure on the rates of sensible heating and evapotranspiration to assess the potential feedbacks to climate if high-latitude warming were to change the distribution of these vegetation types. Measurements were made at Council on the Seward Peninsula, Alaska, at representative tundra, low shrub, tall shrub, woodland (treeline), and boreal forest sites. Structural differences across the transition from tundra to forest included an increase in the leaf area index (LAI) from 0.52 to 2.76, an increase in canopy height from 0.1 to 6.1 m, and a general increase in canopy complexity. These changes in vegetation structure resulted in a decrease in albedo from 0.19 to 0.10 as well as changes to the partitioning of energy at the surface. Bulk surface resistance to water vapor flux remained virtually constant across sites, apparently because the combined soil and moss evaporation decreased while transpiration increased along the transect from tundra to forest. In general, sites became relatively warmer and drier along the transect with the convective fluxes being increasingly dominated by sensible heating, as evident by an increasing Bowen ratio from 0.94 to 1.22. The difference in growing season average daily sensible heating between tundra and forest was 21 W m-2. Fluxes changed non-linearly along the transition, with both shrubs and trees substantially enhancing heat transfer to the atmosphere. These changes in vegetation structure that increase sensible heating could feed back to enhance warming at local to regional scales. The magnitude of these vegetation effects on potential high-latitude warming is two to three times greater than suggested by previous modeling studies. ?? 2005 Elsevier B.V. All rights reserved.
Eddy covariance (EC) estimates of carbon dioxide (CO 2 ) fluxes and energy balance are examined to investigate the functional responses of a mature mangrove forest to a disturbance generated by Hurricane Wilma on October 24, 2005 in the Florida Everglades. At the EC site, high winds from the hurricane caused nearly 100% defoliation in the upper canopy and widespread tree mortality. Soil temperatures down to -50 cm increased, and air temperature lapse rates within the forest canopy switched from statically stable to statically unstable conditions following the disturbance. Unstable conditions allowed more efficient transport of water vapor and CO 2 from the surface up to the upper canopy layer. Significant increases in latent heat fluxes (LE) and nighttime net ecosystem exchange (NEE) were also observed and sensible heat fluxes (H) as a proportion of net radiation decreased significantly in response to the disturbance. Many of these impacts persisted through much of the study period through 2009. However, local albedo and MODIS (Moderate Resolution Imaging Spectro-radiometer) data (the Enhanced Vegetation Index) indicated a substantial proportion of active leaf area recovered before the EC measurements began 1 year after the storm. Observed changes in the vertical distribution and the degree of clumping in newly emerged leaves may have affected the energy balance. Direct comparisons of daytime NEE values from before the storm and after our measurements resumed did not show substantial or consistent differences that could be attributed to the disturbance. Regression analyses on seasonal time scales were required to differentiate the storm's impact on monthly average daytime NEE from the changes caused by interannual variability in other environmental drivers. The effects of the storm were apparent on annual time scales, and CO 2 uptake remained approximately 250 g C m -2 yr -1 lower in 2009 compared to the average annual values measured in 2004–2005. Dry season CO 2 uptake was relatively more affected by the disturbance than wet season values. Complex leaf regeneration dynamics on damaged trees during ecosystem recovery are hypothesized to lead to the variable dry versus wet season impacts on daytime NEE. In contrast, nighttime CO 2 release (i.e., nighttime respiration) was consistently and significantly greater, possibly as a result of the enhanced decomposition of litter and coarse woody debris generated by the storm, and this effect was most apparent in the wet seasons compared to the dry seasons. The largest pre- and post-storm differences in NEE coincided roughly with the delayed peak in cumulative mortality of stems in 2007–2008. Across the hurricane-impacted region, cumulative tree mortality rates were also closely correlated with declines in peat surface elevation. Mangrove forest–atmosphere interactions are interpreted with respect to the damage and recovery of stand dynamics and soil accretion processes following the hurricane.
Estimation of irrigation water use provides essential information for the management and conservation of agricultural water resources. Conventionally, water use data are created based on reports and surveys from water users, whereas manual records may not be complete due to lacking flow meters, measurement gaps, inconsistent methods across regions, and time- and cost-consuming data processing. Alternatively, spatially explicit estimation of irrigation water use can be conducted efficiently using remote sensing evapotranspiration (ET) modeling approaches. In this study, we created a gridded blue water evapotranspiration (BWET) dataset to estimate historical irrigation water consumption (1986 – 2020) in the croplands across the United States High Plains aquifer region. The BWET data were generated by integrating an energy-balance ET model [Operational Simplified Surface Energy Balance model (SSEBop)] and a water-balance ET model [Vegetation ET model (VegET)]. BWET in croplands indicates crop consumptive use of irrigation water extracted from surface water and groundwater resources. The BWET estimates were compared with reported irrigation water use data for all counties within the aquifer region. The results revealed high agreement between growing season (May – September) BWET and annual water withdrawal at county level. Specifically, correlation coefficients of volumetric BWET and water withdrawal were 0.90 and 0.96, respectively, for the entire aquifer region and western Kansas. The timeseries of BWET and water withdrawal showed similar temporal trends and high covariations. The BWET estimates were systematically lower than the water withdrawal measurements, which was primarily attributed to blue water losses in the irrigation system. The irrigation efficiency, calculated as the ratio of BWET to water withdrawal depth, was 0.57 and 0.74 for the entire aquifer region and western Kansas, respectively. This study demonstrates the capability of using satellite-based ET models (e.g., SSEBop and VegET) to efficiently estimate crop water consumption and evaluate irrigation efficiency at landscape, county, and regional scales.
Global energy demands continue to result in new and emerging sources of anthropogenic disturbance to populations and systems. Here, we assessed the influence of natural gas development on a critical component of fitness (nest survival) for Brewer’s sparrow ( Spizella breweri ), sagebrush sparrow ( Artemisiospiza nevadensis ), and sage thrasher ( Oreoscoptes montanus ), three species of sagebrush-obligate songbirds that are of conservation concern, and assessed the efficacy of a commonly used index of oil and gas development intensity (well density) for estimating habitat transformation and predicting species’ responses. During 2008–2009 and 2011–2012 we monitored 926 nests within two natural gas fields in western Wyoming, USA. We calculated landscape metrics (habitat loss, amount of edge, patch shape complexity, and mean patch size) to identify the aspect of landscape transformation most captured by well density. Well density was most positively associated with the amount of sagebrush habitat loss within 1 square kilometer. Nest survival was relatively invariant with respect to well density for all three species. In contrast, nest survival rates of all three species generally decreased with surrounding habitat loss due to energy development. Thus, although well density and habitat loss were strongly correlated, well density resulted in overly conservative estimates of nest survival probability. Our results emphasize the importance of careful evaluation of the appropriateness of particular indices for quantifying the effects of human-induced habitat change. For managers concerned about the effects of natural gas development or similar forms of human land use to co-occurring breeding birds, we recommend minimizing the amount of associated habitat conversion.
Spatial aspects of wildlife responses to human-induced habitat change have been examined frequently, yet the temporal dynamics of responses remain less understood. We tested alternative hypotheses for how the abundance of a suite of declining songbirds in relation to energy development changed over time. We conducted point counts at two natural gas fields during two periods spanning a decade (2008–2009 and 2018–2019), and compared the abundance of sagebrush songbirds across a gradient of surface disturbance between study periods (trend-by-time). We also assessed changes in the abundance of birds between study periods relative to additional development that had occurred (trend-over-time). We predicted that abundance responses to surface disturbance would be more negative during the second period, regardless of additional disturbance that had occurred, because of previously observed inverse relationships between surface disturbance and nest survival at our sites. Contrary to our predictions, abundance responses attenuated by the second time period for two of three species, Brewer's sparrow and sage thrasher (the latter at one energy field only). Sagebrush sparrow abundance, however, consistently decreased with surface disturbance within and between periods. Sage thrasher abundance consistently decreased with surface disturbance at one of the gas fields, and the probability of colonization by thrashers between study periods was lower where additional surface disturbance had occurred. Our results highlight the importance of revisiting wildlife responses to anthropogenic habitat changes over time, to clarify the severity and longevity of effects.
Wind energy development is rapidly expanding in North America, often accompanied by requirements to survey potential facility locations for existing wildlife. Within the USA, golden eagles ( Aquila chrysaetos ) are among the most high-profile species of birds that are at risk from wind turbines. To m inimize golden eagle fatalities in areas proposed for wind development, modified point count surveys are usually conducted to estimate use by these birds. However, it is not always clear what drives variation in the relationship between on-site point count data and actual use by eagles of a wind energy project footprint. We used existing GPS-GSM telemetry data, collected at 15 min intervals from 13 golden eagles in 2012 and 2013, to explore the relationship between point count data and eagle use of an entire project footprint. To do this, we overlaid the telemetry data on hypothetical project footprints and simulated a variety of point count sampling strategies for those footprints. We compared the time an eagle was found in the sample plots with the time it was found in the project footprint using a metric we called “error due to sampling”. Error due to sampling for individual eagles appeared to be influenced by interactions between the size of the project footprint (20, 40, 90 or 180 km 2 ) and the sampling type (random, systematic or stratified) and was greatest on 90 km 2 plots. However, use of random sampling resulted in lowest error due to sampling within intermediate sized plots. In addition sampling intensity and sampling frequency both influenced the effectiveness of point count sampling. Although our work focuses on individual eagles (not the eagle populations typically surveyed in the field), our analysis shows both the utility of simulations to identify specific influences on error and also potential improvements to sampling that consider the context-specific manner that point counts are laid out on the landscape.
We present a Dynamic Energy Budget (DEB) model for the eastern oyster, Crassostrea virginica , which enables the inclusion of salinity as a third environmental variable, on top of the standard foodr and temperature variables. Salinity changes have various effects on the physiology of oysters, potentially altering filtration and respiration rates, and ultimately impacting growth, reproduction and mortality. We tested different hypotheses as to how to include these effects in a DEB model for C. virginica . Specifically, we tested two potential mechanisms to explain changes in oyster shell growth (cm), tissue dry weight (g) and gonad dry weight (g) when salinity moves away from the ideal range: 1) a negative effect on filtration rate and 2) an additional somatic maintenance cost. Comparative simulations of shell growth, dry tissue biomass and dry gonad weight in two monitored sites in coastal Louisiana experiencing salinity from 0 to 28 were statistically analyzed to determine the best hypothesis. Model parameters were estimated through the covariation method, using literature data and a set of specifically designed ecophysiological experiments. The model was validated through independent field studies in estuaries along the northern Gulf of Mexico. Our results suggest that salinity impacts C. virginica ’s energy budget predominantly through effects on filtration rate. With an overwhelming number of environmental factors impacting organisms, and increasing exposure to novel and extreme conditions, the mechanistic nature of the DEB model with its ability to incorporate more than the standard food and temperature variables provides a powerful tool to verify hypotheses and predict individual organism performance across a range of conditions.
Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.
Oil and natural gas development in the western United States has increased substantially in recent decades as technological advances like horizontal drilling and hydraulic fracturing have made extraction more commercially viable. Oil and gas pads are often developed for production, and then capped, reclaimed, and left to recover when no longer productive. Understanding the rates, controls, and degree of recovery of these reclaimed well sites to a state similar to pre-development conditions is critical for energy development and land management decision processes. Here we use a multi-decadal time series of satellite imagery (Landsat 5, 1984–2011) to assess vegetation regrowth on 365 abandoned well pads located across the Colorado Plateau in Utah, Colorado, and New Mexico. We developed high-frequency time series of the Soil-Adjusted Total Vegetation Index (SATVI) for each well pad using the Google Earth Engine cloud computing platform. BFAST time-series models were used to fit temporal trends, identifying when vegetation was cleared from the site and the magnitudes and rates of vegetation change after abandonment. The time series metrics are used to calculate the relative fractional vegetation cover (RFVC) of each pad, a measure of post-abandonment vegetation cover relative to pre-drilling condition. Mean and median RFVC were 36% (s.d. 33%) and 26%, respectively, five years after abandonment, with one third of well pads having RFVC greater than 50%. Statistical analyses suggest that much of the high vegetation cover is associated with weedy invasive annual species such as cheatgrass (Bromus tectorum) and Russian thistle (Salsola spp.). Climate conditions and the year of abandonment also play a role, with increased cover in later years associated with a wetter period. Non-linear change at many pads suggests longer recovery times than would be estimated by linear extrapolation. New techniques implemented here address a complex response of cover change to soils, management, and climate over time, and can be extended to the operational monitoring of energy development across large areas.
Energy-related infrastructure and other human enterprises within sagebrush steppe of the American West often results in changes that promote common raven ( Corvus corax ; hereafter, raven) populations. Ravens, a generalist predator capable of behavioral innovation, present a threat to many species of conservation concern. We evaluate the effects of detailed features of an altered landscape on the probability of raven occurrence using extensive raven survey ( n = 1045) and mapping data from southern Idaho, USA. We found nonlinear relationships between raven occurrence and distances to transmission lines, roads, and facilities. Most importantly, raven occurrence was greater with presence of transmission lines up to 2.2 km from the corridor.We further explain variation in raven occurrence along anthropogenic features based on the amount of non-native vegetation and cover type edge, such that ravens select fragmented sagebrush stands with patchy, exotic vegetative introgression. Raven occurrence also increased with greater length of edge formed by the contact of big sagebrush ( Artemisia tridentate spp.) with non-native vegetation cover types. In consideration of increasing alteration of sagebrush steppe, these findings will be useful for planning energy transmission corridor placement and other management activities where conservation of sagebrush obligate species is a priority.
The Columbia River Littoral Cell (CRLC), a high-wave-energy littoral system, extends 160 km alongshore, generally north of the large Columbia River, and 10–15 km in across-shelf distance from paleo-beach backshores to about 50 m present water depths. Onshore drill holes (19 in number and 5–35 m in subsurface depth) and offshore vibracores (33 in number and 1–5 m in subsurface depth) constrain inner-shelf sand grain sizes (sample means 0.13–0.25 mm) and heavy mineral source indicators (> 90% Holocene Columbia River sand) of the inner-shelf facies (≥ 90% fine sand). Stratigraphic correlation of the transgressive ravinement surface in onshore drill holes and in offshore seismic reflection profiles provide age constraints (0–12 ka) on post-ravinement inner-shelf deposits, using paleo-sea level curves and radiocarbon dates. Post-ravinement deposit thickness (1–50 m) and long-term sedimentation rates (0.4–4.4 m ka − 1 ) are positively correlated to the cross-shelf gradients (0.36–0.63%) of the transgressive ravinement surface. The total post-ravinement fill volume of fine littoral sand (2.48 × 10 10 m 3 ) in the inner-shelf represents about 2.07 × 10 6 m 3 year − 1 fine sand accumulation rate during the last 12 ka, or about one third of the estimated middle- to late-Holocene Columbia River bedload or sand discharge (5–6 × 10 6 m 3 year − 1 ) to the littoral zone. The fine sand accumulation in the inner-shelf represents post-ravinement accommodation space resulting from 1) geometry and depth of the transgressive ravinement surface, 2) post-ravinement sea-level rise, and 3) fine sand dispersal in the inner-shelf by combined high-wave-energy and geostrophic flow/down-welling drift currents during major winter storms.
Dam management often involves tradeoffs among hydropower generation capacity, environmental impacts, and project costs. However, our understandings of such tradeoffs under a full range of dam management options remain limited, which hinders our ability to make sound and scientifically defensible dam management decisions. In order to assess the scope for theoretical tradeoffs, a dynamic model of hydropower production, important fish populations, and project costs was developed using the system dynamics modeling technique. Three dam management options investigated the likely outcomes from: dam removal, fishway installation (e.g., pool-and-weir, Denil, and fish lift), and no action. The model was applied to the Penobscot River located in Maine, United States as a proof of concept, where recent actions (i.e., dam removal and fishway construction) have been undertaken. We modeled theoretical influence of these actions on four significant sea-run fish (alewife Alosa pseudoharengus , American shad Alosa sapidissima , Atlantic salmon Salmo salar , and sea lamprey Petromyzon marinus ) by developing an index of spawner population potential based on population models for each species. Optimal dam management solutions may maximize spawner population potential and energy production to 60-62% of maximum achievable values while limiting the project cost to US$17 million (44% of the maximum value). Our results demonstrate that basin-scale management strategies may increase the migratory fish restoration while preserving hydropower generation capacity. Diversification of management options (e.g., combination of fishway installations, dam removals, and generation capacity) may increase the efficacy of strategic fish-energy-cost tradeoffs.
Exploration and extraction of oil and natural gas have increased in recent years and are expected to expand in the future. Reduction in water quality from energy extraction may negatively affect water supply for agriculture and urban use within catchments as well as down river. We used non-invasive genetic techniques and capture–recapture modeling to estimate the abundance and density of North American river otters ( Lontra canadensis ), a sentinel species of aquatic ecosystems, in Southwestern Wyoming. While densities in two of three river reaches were similar to those reported in other freshwater systems in the western US (1.45–2.39 km per otter), otters appeared to avoid areas near energy development. We found no strong difference in habitat variables, such as overstory cover, at the site or reach level. Also, fish abundance was similar among the three river reaches. Otter activity in our study area could have been affected by elevated levels of disturbance surrounding the industrial gas fields, and by potential surface water contamination as indicated by patterns in water conductivity. Continued monitoring of surface water quality in Southwestern Wyoming with the aid of continuously recording devices and sentinel species is warranted.
To inform responsible energy development, it is important to understand the ecological effects of contamination events. Wastewaters, a common byproduct of oil and gas extraction, often contain high concentrations of sodium chloride (NaCl) and heavy metals (e.g., strontium and vanadium). These constituents can negatively affect aquatic organisms, but there is scarce information for how wastewaters influence potentially distinct microbiomes in wetland ecosystems . Additionally, few studies have concomitantly investigated effects of wastewaters on the habitat (water and sediment) and skin microbiomes of amphibians or relationships among these microbial communities. We sampled microbiomes of water, sediment, and skin of four larval amphibian species across a gradient of chloride contamination (0.04–17,500 mg/L Cl) in the Prairie Pothole Region of North America. We detected 3129 genetic phylotypes and 68 % of those phylotypes were shared among the three sample types. The most common shared phylotypes were Proteobacteria, Firmicutes, and Bacteroidetes. Salinity of wastewaters increased dissimilarity within all three microbial communities, but not the diversity or richness of water and skin microbial communities. Strontium was associated with lower diversity and richness of sediment microbial communities, but not those of water or amphibian skin, likely because metal deposition occurs in sediment when wetlands dry. Based on Bray Curtis distance matrices, sediment microbiomes were similar to those of water, but neither had substantial overlap with amphibian microbiomes. Species identity was the strongest predictor of amphibian microbiomes; frog microbiomes were similar but differed from that of the salamander, whose microbiome had the lowest richness and diversity. Understanding how effects of wastewaters on the dissimilarity, richness, and diversity of microbial communities also influence the ecosystem function of communities will be an important next step. However, our study provides novel insight into the characteristics of, and associations among, different wetland microbial communities and effects of wastewaters from energy production.
Projections for deep decarbonization require large amounts of solar energy, which may compete with other land uses such as agriculture, urbanization, and conservation of natural lands. Existing capacity expansion models do not integrate land use land cover change (LULC) dynamics into projections. We explored the interaction between projected LULC, solar photovoltaic (PV) deployment, and solar impacts on natural lands and croplands by integrating projections of LULC with a model that can project future deployment of solar PV with high spatial resolution for the conterminous United States. We used scenarios of LULC projections from the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios from 2010 to 2050 and two electricity grid scenarios to model future PV deployment and compared those results against a baseline that held 2010 land cover constant through 2050. Though solar PV's overall technical potential was minimally impacted by LULC scenarios, deployed PV varied by −16.5 to 11.6 % in 2050 from the baseline scenario. Total land requirements for projected PV were similar to other studies, but measures of PV impacts on natural systems depended on the underlying land change dynamics occurring in a scenario. The solar PV deployed through 2050 resulted in 1.1 %–2.4 % of croplands and 0.3 %–0.7 % of natural lands being converted to PV. However, the deepest understanding of PV impacts and interactions with land cover emerged when the complete net gains and losses from all land cover change dynamics, including PV, were integrated. For example, one of the four LULC projections allows for high solar development and a net gain in natural lands, even though PV drives a larger percentage of natural land conversion. This paper shows that integrating land cover change dynamics with energy expansion models generates new insights into trade offs between decarbonization, impacts of renewables, and ongoing land cover change.