The impact of electric passenger transport technology under an economy-wide climate policy in the United States: Carbon dioxide emissions,coal use,and carbon dioxide capture and storage

Plug-in hybrid electric vehicles (PHEVs) have the potential to be an economic means of reducing direct (or tailpipe) carbon dioxide (CO₂) emissions from the transportation sector. However, without a climate policy that places a limit on CO₂ emissions from the electric generation sector, the net impact of widespread deployment of PHEVs on overall U.S. CO₂ emissions is not as clear. A comprehensive analysis must consider jointly the transportation and electricity sectors, along with feedbacks to the rest of the energy system. In this paper, we use the Pacific Northwest National Laboratory's MiniCAM model to perform an integrated economic analysis of the penetration of PHEVs and the resulting impact on total U.S. CO₂ emissions. In MiniCAM, the deployment of PHEVs (or any technology) is determined based on its relative economics compared to all other methods of providing fuels and energy carriers to serve passenger transportation demands. Under the assumptions used in this analysis where PHEVs obtain 50–60% of the market for passenger automobiles and light-duty trucks, the ability to deploy PHEVs under the two climate policies modelled here results in over 400 million tons (MT) CO₂ per year of additional cost-effective emissions reductions from the U.S. economy by 2050. In addition to investments in nuclear and renewables, one of the key technology options for mitigating emissions in the electric sector is CO₂ capture and storage (CCS). The additional demand for geologic CO₂ storage created by the introduction of the PHEVs is relatively modest: approximately equal to the cumulative geologic CO₂ storage demanded by two to three large 1000 megawatt (MW) coal-fired power plants using CCS over a 50-year period. The introduction of PHEVs into the U.S. transportation sector, coupled with climate policies such as those examined here, could also reduce U.S. demand for oil by 20–30% by 2050 compared to today's levels.     

Natural area visitors' place meaning and place attachment ascribed to a marine setting

Investigations of place have often focused on either place meaning (utilizing interpretive designs) or place attachment (using quantitative measures). Rarely have researchers explored the association between place meaning and place attachment. Hence, this investigation was designed to explore how individuals' attachment to a natural environment is reflected in their depictions of why the resource is meaningful.     

Summer Temperature Patterns in Headwater Streams of the Oregon Coast Range1

Abstract: Cool summertime stream temperature is an important component of high quality aquatic habitat in Oregon coastal streams. Within the Oregon Coast Range, small headwater streams make up a majority of the stream network; yet, little information is available on temperature patterns and the longitudinal variability for these streams. In this paper we describe preharvest spatial and temporal patterns in summer stream temperature for small streams of the Oregon Coast Range in forests managed for timber production. We also explore relationships between stream and riparian attributes and observed stream temperature conditions and patterns. Summer stream temperature, channel, and riparian data were collected on 36 headwater streams in 2002, 2003, and 2004. Mean stream temperatures were consistent among summers and generally warmed in a downstream direction. However, longitudinal trends in maximum temperatures were more variable. At the reach scale of 0.5‐1.7 km, maximum temperatures increased in 17 streams, decreased in seven streams and did not change in three reaches. At the subreach scale (0.1‐1.5 km), maximum temperatures increased in 28 subreaches, decreased in 14, and did not change in 12 subreaches. Models of increasing temperature in a downstream direction may oversimplify fine‐scale patterns in small streams. Stream and riparian attributes that correlated with observed temperature patterns included cover, channel substrate, channel gradient, instream wood jam volume, riparian stand density, and geology type. Longitudinal patterns of stream temperature are an important consideration for background characterization of water quality. Studies attempting to evaluate stream temperature response to timber harvest or other modifications should quantify variability in longitudinal patterns of stream temperature prior to logging.     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.     

The Influence of the Pacific Decadal Oscillation on Annual Floods in the Rivers of Western Canada

We analyzed annual peak flow series from 127 naturally flowing or naturalized streamflow gauges across western Canada to examine the impact of the Pacific Decadal Oscillation (PDO) on annual flood risk, which has been previously unexamined in detail. Using Spearman's rank correlation ρ and permutation tests on quantile‐quantile plots, we show that higher magnitude floods are more likely during the negative phase of the PDO than during the positive phase (shown at 38% of the stations by Spearman's rank correlations and at 51% of the stations according to the permutation tests). Flood frequency analysis (FFA) stratified according to PDO phase suggests that higher magnitude floods may also occur more frequently during the negative PDO phase than during the positive phase. Our results hold throughout much of this region, with the upper Fraser River Basin, the Columbia River Basin, and the North Saskatchewan River Basin particularly subject to this effect. Our results add to other researchers' work questioning the wholesale validity of the key assumption in FFA that the annual peak flow series at a site is independently and identically distributed. Hence, knowledge of large‐scale climate state should be considered prior to the design and construction of infrastructure.     

新疆雪豹种群密度监测方法探讨

2004-2010年间,前后累计270多天,新疆雪豹研究小组在新疆北塔山、阿尔泰山、昆仑山、天山东部和托木尔峰地区20多个地点(山谷),对雪豹(Uncia uncia)的痕迹进行了全面调查,共计完成150多条样线,总长度接近190 km,痕迹数平均为1～3个·km-1.记录到的痕迹有粪团、嗅痕(气味标记)、足迹链、刨痕(刨坑)、爪痕、卧迹、毛发、尿迹、血迹、剩余食物(动物尸体)和吼声等.通过痕迹学的分析,初步掌握雪豹的领域范围、分布规律和相对密度.之后开展了红外相机拍摄、雪豹食物资源普查、市场毛皮调查、贸易通道调查、杀戮案件搜集、民间问卷调查、非政府组织(NGO)社区服务与牧业冲突调研等工作.同期布设红外相机36台,约2094个照相日,计50 256 h,回收胶卷71个,回收清晰雪豹照片32张,平均拍摄率或"捕获率"(capture rate)达1.53%.确定在托木尔峰250 km2范围内有5～8只雪豹活动,密度为2.0～3.2只·(100 km2)-1.在比较分析各种监测结果的基础上,讨论了新疆雪豹种群密度不同监测方法的优点与局限性.     

Multivariate trade-offs, succession, and phenological differentiation in a guild of colonial invertebrates

For competing species limited by one or few resources, diversity is thought to be maintained by trade-offs that allow niche differentiation without resource partitioning. However, few studies have quantified multiple key traits for each species in a guild and shown that trade-offs among these traits apply across the guild. Here we document strong bivariate and multivariate relationships among growth rate, fecundity, longevity, and overgrowth ability for six co-occurring colonial invertebrates. We find that all four of these traits are constrained to a single "fast-slow" niche axis that mechanistically relates life history variation to a colonization-competition trade-off. The location of species on this axis strongly predicts the timing of their peak abundance during succession. We also find that species closer to each other on the fast-slow axis are more likely to differ in reproductive phenology, suggesting a secondary dimension of niche differentiation for otherwise similar species.     

Arsenic in North Carolina: public health implications

Arsenic is a known human carcinogen and relevant environmental contaminant in drinking water systems. We set out to comprehensively examine statewide arsenic trends and identify areas of public health concern. Specifically, arsenic trends in North Carolina private wells were evaluated over an eleven-year period using the North Carolina Department of Health and Human Services database for private domestic well waters. We geocoded over 63,000 domestic well measurements by applying a novel geocoding algorithm and error validation scheme. Arsenic measurements and geographical coordinates for database entries were mapped using Geographic Information System techniques. Furthermore, we employed a Bayesian Maximum Entropy (BME) geostatistical framework, which accounts for geocoding error to better estimate arsenic values across the state and identify trends for unmonitored locations. Of the approximately 63,000 monitored wells, 7712 showed detectable arsenic concentrations that ranged between 1 and 806 μg/L. Additionally, 1436 well samples exceeded the EPA drinking water standard. We reveal counties of concern and demonstrate a historical pattern of elevated arsenic in some counties, particularly those located along the Carolina terrane (Carolina slate belt). We analyzed these data in the context of populations using private well water and identify counties for targeted monitoring, such as Stanly and Union Counties. By spatiotemporally mapping these data, our BME estimate revealed arsenic trends at unmonitored locations within counties and better predicted well concentrations when compared to the classical kriging method. This study reveals relevant information on the location of arsenic-contaminated private domestic wells in North Carolina and indicates potential areas at increased risk for adverse health outcomes.