Rareness and specialization in plant-pollinator networks

Most rare species appear to be specialists in plant-pollinator networks. This observation could result either from real ecological processes or from sampling artifacts. Several methods have been proposed to overcome these artifacts, but they have the limitation of being based on visitation data, causing interactions involving rare visitor species to remain undersampled. We propose the analysis of food composition in bee trap nests to assess the reliability of network specialization estimates. We compared data from a plant-pollinator network in the Monte Desert of Villavicencio Nature Reserve, Argentina, sampled by visit observation, and data from trap nests sampled at the same time and location. Our study shows that trap nest sampling was good for estimating rare species degree. The rare species in the networks appear to be more specialized than they really are, and the bias in the estimation of the species degree increases with the rareness. The low species degree of these rare species in the visitation networks results from insufficient sampling of the rare interactions, which could have important consequences for network structure.     

Transnational environmental problems — The United States,Canada, Mexico

Summary The paper examines the problems associated with transboundary environmental pollution. While briefly recording the efforts of international organizations in this area, the main content of the paper is concerned with an analysis of problems arising between the United States and Mexico, and between the United States and Canada. The paper also discusses new organizational forms that have been developed to bring transboundary issues to a higher policy-making level.Professor Wilcher entered the academic profession after a career in government service. He holds Masters Degrees from West Virginia University and the University of Pittsburgh and a Doctoral Degree from West Virginia University. He is currently Assistant Professor of Political Science at The Pennsylvania State University, New Kensington Campus. He is the author ofEnvironmental Cooperation in the North Atlantic Area published by the University Press of America.     

Integrating lidar and satellite optical depth with ambient monitoring for 3-dimensional particulate characterization

A combination of in-situ PM_2.5, sunphotometers, upward pointing lidar and satellite aerosol optical depth (AOD) instruments have been employed to better understand variability in the correlation between AOD and PM_2.5 at the surface. Previous studies have shown good correlation between these measures, especially in the US east, and encouraged the use of satellite data for spatially interpolating between ground sensors. This work shows that cases of weak correlation can be better understood with knowledge of whether the aerosol is confined to the surface planetary boundary layer (PBL) or aloft. Lidar apportionment of the fraction of aerosol optical depth that is within the PBL can be scaled to give better agreement with surface PM_2.5 than does the total column amount. The study has shown that lidar combined with surface and remotely sensed data might be strategically used to improve our understanding of long-range or regionally transported pollutants in multiple dimensions.     

THE COST OF PEAK CAPACITY WATER1

ABSTRACT: Calgary, the fastest growing city in Canada, is about to expand its urban water supply facilities in order to meet peak summer demands. Most of Calgary's residential water is sold by flat rate. The effect of this pricing policy on peak and average demands is discussed. The true marginal cost of peak capacity from the new expansion is calculated. The effect of a proposed metering program on capacity expansion requirements is computed. It is concluded that metering should preceed the next capacity expansion.     

Predicting arsenic concentrations in groundwater of San Luis Valley,Colorado: implications for individual-level lifetime exposure assessment

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83–0.92 for samples collected from the same well 15–25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.     

Improving species status assessments under the U.S. Endangered Species Act and implications for multispecies conservation challenges worldwide

Despite its successes, the U.S. Endangered Species Act (ESA) has proven challenging to implement due to funding limitations, workload backlog, and other problems. As threats to species survival intensify and as more species come under threat, the need for the ESA and similar conservation laws and policies in other countries to function efficiently has grown. Attempts by the U.S. Fish and Wildlife Service (USFWS) to streamline ESA decisions include multispecies recovery plans and habitat conservation plans. We address species status assessment (SSA), a USFWS process to inform ESA decisions from listing to recovery, within the context of multispecies and ecosystem planning. Although existing SSAs have a single-species focus, ecosystem-based research can efficiently inform multiple SSAs within a region and provide a foundation for transition to multispecies SSAs in the future. We considered at-risk grassland species and ecosystems within the southeastern United States, where a disproportionate number of rare and endemic species are associated with grasslands. To initiate our ecosystem-based approach, we used a combined literature-based and structured World Café workshop format to identify science needs for SSAs. Discussions concentrated on 5 categories of threats to grassland species and ecosystems, consistent with recommendations to make shared threats a focus of planning under the ESA: (1) habitat loss, fragmentation, and disruption of functional connectivity; (2) climate change; (3) altered disturbance regimes; (4) invasive species; and (5) localized impacts. For each threat, workshop participants identified science and information needs, including database availability, research priorities, and modeling and mapping needs. Grouping species by habitat and shared threats can make the SSA process and other planning processes for conservation of at-risk species worldwide more efficient and useful. We found a combination of literature review and structured discussion effective for identifying the scientific information and analysis needed to support the development of multiple SSAs. Article impact statement: Species status assessments can be improved by an ecosystem-based approach that groups imperiled species by shared habitats and threats.     

The combined effects of on-road and simulator training with feedback on older drivers' on-road performance: Evidence from a randomized controlled trial

Objective: A number of training programs that seek to improve driving performance among older drivers are available accompanied by a growing interest in their effectiveness. The purpose of the present investigation was to examine the combined effect of (1) basic in-class training (BT); (2) on-road training with individualized feedback (OR); and (3) training on a driving simulator (S).

Methods: Using a randomized controlled trial study design, 78 older drivers were randomly assigned to one of 3 groups (BT, BT + OR, or BT + OR + S). All participants completed a pre- and postintervention on-road driving evaluation on a standardized route. The driving evaluations were recorded using video and Global Positioning System (GPS) equipment and were scored by a blind assessor.

Results: The results indicated a significant reduction of approximately 30% in overall number of driving errors/omissions among participants in the BT + OR and the BT + OR + S groups in comparison to participants in the BT group.

Conclusions: This study adds to the mounting evidence demonstrating the effectiveness of individualized driver training in improving safe driving among older adults.